The late Arthur Silver Morton has contributed immensely to our understanding and preservation of western Canadian history. One of Mortons joys was locating remains of long forgotten fur trade posts. As a result, a large number of the Saskatchewan fur trade posts that we know of were located and recorded by Morton. The majority of Mortons investigations took place throughout the 1930s and 1940s. Morton consulted whatever historic sources were available to him at the time: numerous historic documents, ethnographic accounts and local histories.<p> There has been archaeological evidence that suggests Morton misidentified numerous fur trade post sites. For example, research at the Hudsons Bay Companys South Branch House (1786-1794), which Morton identified in 1944, has sparked some controversy as to whether or not it is that particular post. As a result, this provides the author with an excellent chance to examine how Morton identified Saskatchewan fur trade posts and to determine through archaeological excavations and historical documents the accuracy of Mortons historical site designation at South Branch House.<p> A critical approach to Mortons work will determine how accurate his work is for contemporary archaeological investigations of fur trade posts. Furthermore, this thesis may provide historical archaeologists with insights as to how to go about identifying fur trade posts, which will contribute to our overall understanding of the western Canadian fur trade.

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The maximum weight-independent set problem (MWISP) is one of the most well-known and well-studied NP-hard problems in the field of combinatorial optimization. In the first part of the dissertation, I explore efficient branch-and-price (B&P) approaches to solve MWISP exactly. B&P is a useful integer-programming tool for solving NP-hard optimization problems. Specifically, I look at vertex- and edge-disjoint decompositions of the underlying graph. MWISP’s on the resulting subgraphs are less challenging, on average, to solve. I use the B&P framework to solve MWISP on the original graph G using these specially constructed subproblems to generate columns. I demonstrate that vertex-disjoint partitioning scheme gives an effective approach for relatively sparse graphs. I also show that the edge-disjoint approach is less effective than the vertex-disjoint scheme because the associated DWD reformulation of the latter entails a slow rate of convergence. In the second part of the dissertation, I address convergence properties associated with Dantzig-Wolfe Decomposition (DWD). I discuss prevalent methods for improving the rate of convergence of DWD. I also implement specific methods in application to the edge-disjoint B&P scheme and show that these methods improve the rate of convergence. In the third part of the dissertation, I focus on identifying new cut-generation methods within the B&P framework. Such methods have not been explored in the literature. I present two new methodologies for generating generic cutting planes within the B&P framework. These techniques are not limited to MWISP and can be used in general applications of B&P. The first methodology generates cuts by identifying faces (facets) of subproblem polytopes and lifting associated inequalities; the second methodology computes Lift-and-Project (L&P) cuts within B&P. I successfully demonstrate the feasibility of both approaches and present preliminary computational tests of each.

The International Monetary Fund points out that four kinds of financial crisis in the world financial markets currency crisis, external debt crisis, bank crisis and systematic crisis . Taiwan could be happened in bank crisis and could have potentially impaired the economies of Taiwan. That was reason why Government protected banking industry avoiding collapse and bankruptcy. This paper details why Private Equity Fund M&A Taiwan domestic bank and the effects on financial markets. Since 2006 Carlyle Group one of a global private equity investment firm takeover bid for Advanced Semiconductor Engineering Inc (¤é¤ë¥ú¥b¾ÉÅé)--the world's top chip packager for US$5.45 billion- Private Equity Firm had known for Taiwan financial markets. The Government refused the plan due to that takeover bid may weakening the local capital market and leading to an outflow of investment into China. Foreign investment in Taiwan's banking industry is not new, but the acquisition of domestic banks has only become available to Private Equity Fund recently. The domestic banking industry has become a lucrative target for foreign investors not only of the Government has a policy of limiting the quantity of banking branches but also lower P/B in Asia region. Since 1997s, a striking feature in the development of Taiwan banking industry structure is the significant decline in the performance of banks while the steadily increase in the number of bank branches and caused by overbanking in Taiwan. As Taiwan slowly opens its banking industry after second round banking reformation in 2001, global M&A trends also had impacts on Taiwan, foreign financial institutions are increasingly looking to make strategic and financial investments. This paper gives a brief description of the development in the past 10 years, analyzes the driving forces on the merger of financial institutions From this research, we could come to the conclusions as follows: 1. A financial investment in domestic banks is a win-win for the various parties Private equity fund M&A of domestic commercial banks not only a very good source of capital in Taiwan, but also, through the competition of foreign banks, stimulates domestic financial institutions to upgrade operational skills and management, and improve operational efficiency and competitiveness, thus contributing to the upgrading of the financial system. 2. This paper using threshold regression model to find an adequate branch numbers of Commercial Banks industry in Taiwan. We found significant evidence good for the shareholders equity only when the branch numbers are larger than 88. 3. On the view of bank branch, the next target acquired company is Far Eastern International Bank(35 branches) ,Jih Sun Bank(36 branches) , King¡¥s Town Bank(62 branches) ,Taichung Commercial Bank(78 branches).ABN AMRO Bank(Taiwan)M&A Taitung Business Bank, the branches from 5 to 37, not to meet the bank's need for scale economics in Taiwan markets and should be M&A again 4. Private Equity Fund aims to pursue long term total return primarily through investment in equities and equity-related securities but had unique niche in resolving banking risk and corporate governance. also capitalized on the recovery of financial markets after the financial crisis in Taiwan banking indusdry According to experience of Private-Equity Firm to merge to banking industry in Korea Private Equity Fund exit their investments at last within 5-7 years after turned the bank successfully around 5. It's difference type of entering the Taiwan market through the acquisitions of banks, one is strategic investment (e.g.,Citigroup and Standard Chartered) and financial players (e.g., Newbridge Capital, The Carlyle Group).Strategic investment made a goal to construct a plateform to link Taiwan and China

Interwell connectivity is a very important piece of the puzzle for petroleum engineers. To optimize the injection well flow for increasing the production rate, interwell connectivity is a very important parameter. To build a model that works with better precision and with less effort has always been desired by reservoir engineers. In this study we developed an electric circuit network model (referred as the admittance or ymodel) for calculating the admittance parameters to predict branch flow rates (injectorproducer well pair) of oil reservoirs with precision. The y-model is very simple and efficient model that can predict branch flow very efficiently. Injection and production flow rates are the key data used in this model, which also happens to be the most abundant data for oil reservoirs. Injector well bottom-hole pressure data can also be used in this model if available. The governing equation of the electric circuit analogy of well to well flow rates in the oil reservoir is based on Ohm’s law for admittance. A mathematical procedure is also being developed for this circuit network model which solves a series of equations and finds unique solutions for the admittances and branch flows. These results can further be used for predicting the production flow rate for individual producer well. The model shows very good agreement with the exploration data of real oil reservoir. / text

For decades, the semiconductor industry enjoyed exponential improvements in microprocessor power and performance with the device scaling of successive technology generations. Scaling limitations at sub-micron technologies, however, have ceased to provide these historical performance improvements within a limited power budget. While device scaling provides a larger number of transistors per chip, for the same chip area, a growing percentage of the chip will have to be powered off at any given time due to power constraints. As such, the architecture community has focused on energy-efficient designs and is looking to specialized hardware to provide gains in performance. A focus on energy efficiency, along with increasingly less reliable transistors due to device scaling, has led to research in the area of approximate computing, where accuracy is traded for energy efficiency when precise computation is not required. There is a growing body of approximation-tolerant applications that, for example, compute on noisy or incomplete data, such as real-world sensor inputs, or make approximations to decrease the computation load in the analysis of cumbersome data sets. These approximation-tolerant applications span application domains, such as machine learning, image processing, robotics, and financial analysis, among others. Since the advent of the modern processor, computing models have largely presumed the attribute of accuracy. A willingness to relax accuracy requirements, however, with goal of gaining energy efficiency, warrants the re-investigation of the potential of analog computing. Analog hardware offers the opportunity for fast and low-power computation; however, it presents challenges in the form of accuracy. Where analog compute blocks have been applied to solve fixed-function problems, general-purpose computing has relied on digital hardware implementations that provide generality and programmability. The work presented in this thesis aims to answer the following questions: Can analog circuits be successfully integrated into general-purpose computing to provide performance and energy savings? And, what is required to address the historical analog challenges of inaccuracy, programmability, and a lack of generality to enable such an approach? This thesis work investigates a neural approach as a means to address the historical analog challenges of inaccuracy, programmability, and generality and to enable the use of analog circuits in general-purpose, high-performance computing. The first piece of this thesis work investigates the use of analog circuits at the microarchitecture level in the form of an analog neural branch predictor. The task of branch prediction can tolerate imprecision, as roll-back mechanisms correct for branch mispredictions, and application-level accuracy remains unaffected. We show that analog circuits enable the implementation of a highly-accurate, neural-prediction algorithm that is infeasible to implement in the digital domain. The second piece of this thesis work presents a neural accelerator that targets approximation-tolerant code. Analog neural acceleration provides application speedup of 3.3x and energy savings of 12.1x with a quality loss less than 10% for all except one approximation-tolerant benchmark. These results show that, using a neural approach, analog circuits can be applied to provide performance and energy efficiency in high-performance, general-purpose computing. / text

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In order to understand the origin of globular clusters, large samples of their stars need to be observed and analyzed for their chemical composition. This is especially true for the complex, multimetallic cluster ω Centauri, with its large range of iron, carbon, nitrogen, oxygen, sodium and barium abundances. In order to accomplish this, an automated spectral matching pipeline was developed to determine these abundances. This thesis made use of photometry and low resolution spectroscopy to analyze the chemical composition of evolved stars in three clusters: ω Cen, 47 Tuc and NGC 6752. The latter two clusters are monometallic and selected due to their similar metallicities to the metal-rich and metal-poor stars in ω Cen. This allowed them to be used as test-cases for the spectral matching pipeline. For ω Cen, two analyses were performed. In the first, 221 giant branch stars were selected that had known [O/Fe]. These stars showed the expected anticorrelation in [C/Fe]to [N/Fe]. In the second, spectral indices were used to estimate the oxygen abundance of the stars, leading to a determination of whether a particular star was oxygen-rich or oxygen-poor. From this a catalogue of abundances of iron, carbon and barium of 848 giant branch stars were determined, of which 557 also had well-defined nitrogen abundances. k-means clustering analysis was used to group the stars in ω Cen into four homogeneous groups based upon these abundances. These groups suggest that there were at least four main periods of star formation in the cluster. The exact order of these star formation events is not yet understood, with some models predicting the groups formed from iron-poorest to iron-richest, while others suggest the potential for iron-poorer groups to form after iron-rich groups. These results compare well with those found from higher resolution studies and show the value of more extensive lower resolution spectral surveys. They also highlight the need for large samples of stars when working with a complex object like ω Cen.