952 resultados para public debt management
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This paper describes the architecture of a computer system conceived as an intelligent assistant for public transport management. The goal of the system is to help operators of a control center in making strategic decisions about how to solve problems of a fleet of buses in an urban network. The system uses artificial intelligence techniques to simulate the decision processes. In particular, a complex knowledge model has been designed by using advanced knowledge engineering methods that integrates three main tasks: diagnosis, prediction and planning. Finally, the paper describes two particular applications developed following this architecture for the cities of Torino (Italy) and Vitoria (Spain).
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In the last few years, technical debt has been used as a useful means for making the intrinsic cost of the internal software quality weaknesses visible. This visibility is made possible by quantifying this cost. Specifically, technical debt is expressed in terms of two main concepts: principal and interest. The principal is the cost of eliminating or reducing the impact of a, so called, technical debt item in a software system; whereas the interest is the recurring cost, over a time period, of not eliminating a technical debt item. Previous works about technical debt are mainly focused on estimating principal and interest, and on performing a cost-benefit analysis. This cost-benefit analysis allows one to determine if to remove technical debt is profitable and to prioritize which items incurring in technical debt should be fixed first. Nevertheless, for these previous works technical debt is flat along the time. However the introduction of new factors to estimate technical debt may produce non flat models that allow us to produce more accurate predictions. These factors should be used to estimate principal and interest, and to perform cost-benefit analysis related to technical debt. In this paper, we take a step forward introducing the uncertainty about the interest, and the time frame factors so that it becomes possible to depict a number of possible future scenarios. Estimations obtained without considering the possible evolution of the interest over time may be less accurate as they consider simplistic scenarios without changes.
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One of the key challenges that Ukraine is facing is the scale of its foreign debt (both public and private). As of 1st April it stood at US$ 126 billion, which is 109.8% of the country’s GDP. Approximately 45% of these financial obligations are short-term, meaning that they must be paid off within a year. Although the value of the debt has fallen by nearly US$ 10 billion since the end of 2014 (due to the private sector paying a part of the liabilities), the debt to GDP ratio has increased due to the recession and the depreciation of the hryvnia. The value of Ukraine’s foreign public debt is also on the rise (including state guarantees); since the beginning of 2015 it has risen from US$ 37.6 billion to US$ 43.6 billion. Ukraine does not currently have the resources to pay off its debt. In this situation a debt restructuring is necessary and this is one of the top priorities for the Ukrainian government as well as for the International Monetary Fund (IMF) and its assistance programme. Without this it will be much more difficult for Ukraine to overcome the economic crisis.
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Shipping list no.: 2001-0272-P.
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Map wanting.
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Mode of access: Internet.
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Description based on: Aug. 31, 1974; title from caption.
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"Prepared with the assistance of Work Projects Administration, official project no. 665-71-3-104."
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Mode of access: Internet.
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Caption title.
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Editors: -Oct. 1920, H. J. Gonden.--Nov. 1920-Nov. 1922, A. W. Park.--Dec. 1922-1933, J. B. Wootan.
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Mode of access: Internet.