The Relation Between Bank Resolutions and Information Environment: Evidence from the Auctions for Failed Banks

This study examines the impact of disclosure requirements on the resolution costs of failed banks. Consistent with the hypothesis that disclosure requirements mitigate information asymmetries in the auctions for failed banks, I find that, when failed banks are subject to more comprehensive disclosure requirements, regulators incur lower costs of closing a bank and retain a lower portion of the failed bank's assets, while bidders that are geographically more distant are more likely to participate in the bidding for the failed bank. The paper provides new insights into the relation between disclosure and the reorganization of a banking system when the regulators' preferred plan of action is to promote the acquisition of undercapitalized banks by healthy ones. The results suggest that disclosure regulation policy influences the cost of resolution of a bank and, as a result, could be an important factor in the definition of the optimal resolution strategy during a banking crisis event.Sanford J. Grossman Fellowship in Honor of Arnold Zellne

A Nonlinear Dynamic Method for Supporting Large-Scale Decision-Making in Uncertain Environments

This research developed a methodology for supporting decision making by reducing uncertainty in decision environments which are too large, dynamic and complex to be treated by traditional quantitative and simulation techniques. These environments are complex because of the free choice associated with human involvement, and the existence of a large number of interrelated factors which influence the outcomes of the decision process. They are dynamic because the ground rules affecting those interrelationships are constantly changing. Uncertainty cannot be treated probabilistically, since identification of a full set of outcomes and factors of influence is not possible. The venue for the investigation was the infrastructure which supports commercial space launch activities in the United States. The issue treated was whether it would be advisable to make large capital investment in that infrastructure. The problem was approached using the principles of Chaos Theory and Nonlinear Dynamics, in a manner similar to that used by Priesmeyer (1992). The intent was to engender a more systemic view of the environment and approach analysis by examining marginal changes, over a period of ten years, in factors which tend to influence the outcome. The objective was to develop hypotheses which, when validated, will provide a new perspective for decision makers from which to enhance the robustness of these kinds of decisions. The methodology, which evolved over several years of preliminary research, involved identification of sectors of the commercial space infrastructure, isolation of the more important decision factors, identification and solicitation of knowledgeable respondents from the various infrastructure sectors, development of a computerized qualitative data gathering instrument, and graphical analysis of data represented by phase plane diagrams. Although there was little evidence of classical chaotic behavior in the data, the analysis was able to isolate those nonlinear dynamic relationships between decision factors which appeared most likely to provide information regarding system behavior. One hypothesis was developed directly from that observation. A second resulted from the development of an aggregate measure of the level of uncertainty (and, consequently, investment risk) inherent in the decision environment

Characterizing the Load Environment of Ferry Landings for Washington State Ferries and the Alaska Marine Highway System

INE/AUTC 13.0

Buoyancy Effects On Building Pressurization In Extreme Cold Climates

Thesis (Ph.D.) University of Alaska Fairbanks, 2003This research investigates building pressurization due to buoyancy effect. The American Society of Heating, Refrigeration, and Air Conditioning Engineers (ASHRAE) presents an idealized equation to calculate the buoyancy effect. This dissertation compares differential pressure measurements from an actual building exposed to extremely cold temperatures to this idealized model. It also presents new statistical models based on the collected data. These new models should provide engineers with improved tools to properly account for building pressurization for designs in extreme cold climates. Building pressurization, the differential pressure between the interior of a building and its exterior surroundings, is an important design consideration. Pressurization is the driving force in building infiltration/exfiltration. It also affects air flow within building zones. Improper calculation of pressurization can result in under-sizing the building's heating and cooling systems, improper operation of air distribution systems, improper operation of elevators, and freezing and failure of water distribution and circulation systems. Building pressurization is affected by: wind (speed and direction), exterior-to-interior temperature difference, and mechanical equipment operation. In extreme cold climates, the predominant effect is air buoyancy due to temperature differences across the building envelope. The larger the temperature difference, the larger the buoyancy effect. In extreme cold climates, the largest temperature differences often occur at times when wind speed is negligible. This dissertation also demonstrates the use of existing data sources such as building automation systems to collect data for basic research. Modern systems automation provides a tremendous amount of data that, in the past, had to be collected through separate instrumentation and data acquisition systems. Taking advantage of existing automation systems can provide the required data at greatly reduced costs when compared to previous industry practices. The statistical analysis approach taken in this research expands the tools for engineering design. Actual interactions of real world variables are analyzed and used to produce prediction models. These techniques allow the model to incorporate relationships which may not be fully understood at the underlying principle level but are evidenced in the data collected from actual installations.* *This dissertation includes a CD that is compound (contains both a paper copy and CD as part of the dissertation). The CD requires the following applications: Internet Browser; Adobe Acrobat; Microsoft Office; Image Viewer

Application of advanced on-board processing concepts to future satellite communications systems

An initial definition of on-board processing requirements for an advanced satellite communications system to service domestic markets in the 1990's is presented. An exemplar system architecture with both RF on-board switching and demodulation/remodulation baseband processing was used to identify important issues related to system implementation, cost, and technology development

State-of-the-art in aerodynamic shape optimisation methods

Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners

Programming language trends : an empirical study

Predicting the evolution of software engineering technology trends is a dubious proposition. The recent evolution of software technology is a prime example; it is fast paced and affected by many factors, which are themselves driven by a wide range of sources. This dissertation is part of a long term project intended to analyze software engineering technology trends and how they evolve. Basically, the following questions will be answered: How to watch, predict, adapt to, and affect software engineering trends? In this dissertation, one field of software engineering, programming languages, will be discussed. After reviewing the history of a group of programming languages, it shows that two kinds of factors, intrinsic factors and extrinsic factors, could affect the evolution of a programming language. Intrinsic factors are the factors that can be used to describe the general desigu criteria of programming languages. Extrinsic factors are the factors that are not directly related to the general attributes of programming languages, but still can affect their evolution. In order to describe the relationship of these factors and how they affect programming language trends, these factors need to be quantified. A score has been assigued to each factor for every programming language. By collecting historical data, a data warehouse has been established, which stores the value of each factor for every programming language. The programming language trends are described and evaluated by using these data. Empirical research attempts to capture observed behaviors by empirical laws. In this dissertation, statistical methods are used to describe historical programming language trends and predict the evolution of the future trends. Several statistics models are constructed to describe the relationships among these factors. Canonical correlation is used to do the factor analysis. Multivariate multiple regression method has been used to construct the statistics models for programming language trends. After statistics models are constructed to describe the historical programming language trends, they are extended to do tentative prediction for future trends. The models are validated by comparing the predictive data and the actual data

Intrinsically Evolvable Artificial Neural Networks

Dedicated hardware implementations of neural networks promise to provide faster, lower power operation when compared to software implementations executing on processors. Unfortunately, most custom hardware implementations do not support intrinsic training of these networks on-chip. The training is typically done using offline software simulations and the obtained network is synthesized and targeted to the hardware offline. The FPGA design presented here facilitates on-chip intrinsic training of artificial neural networks. Block-based neural networks (BbNN), the type of artificial neural networks implemented here, are grid-based networks neuron blocks. These networks are trained using genetic algorithms to simultaneously optimize the network structure and the internal synaptic parameters. The design supports online structure and parameter updates, and is an intrinsically evolvable BbNN platform supporting functional-level hardware evolution. Functional-level evolvable hardware (EHW) uses evolutionary algorithms to evolve interconnections and internal parameters of functional modules in reconfigurable computing systems such as FPGAs. Functional modules can be any hardware modules such as multipliers, adders, and trigonometric functions. In the implementation presented, the functional module is a neuron block. The designed platform is suitable for applications in dynamic environments, and can be adapted and retrained online. The online training capability has been demonstrated using a case study. A performance characterization model for RC implementations of BbNNs has also been presented