A model to forecast financial failure, in non financial galician SMES

We are concerned with providing more empirical evidence on forecast failure, developing forecast models, and examining the impact of events such as audit reports. A joint consideration of classic financial ratios and relevant external indicators leads us to build a basic prediction model focused in non-financial Galician SMEs. Explanatory variables are relevant financial indicators from the viewpoint of the financial logic and financial failure theory. The paper explores three mathematical models: discriminant analysis, Logit, and linear multivariate regression. We conclude that, even though they both offer high explanatory and predictive abilities, Logit and MDA models should be used and interpreted jointly.

Monetary and fiscal policies interactions in a monetary union with country-size asymmetry

Within a country-size asymmetric monetary union, idiosyncratic shocks and national fiscal stabilization policies cause asymmetric cross-border effects. These effects are a source of strategic interactions between noncoordinated fiscal and monetary policies: on the one hand, due to larger externalities imposed on the union, large countries face less incentives to develop free-riding fiscal policies; on the other hand, a larger strategic position vis-à-vis the central bank incentives the use of fiscal policy to, deliberately, influence monetary policy. Additionally, the existence of non-distortionary government financing may also shape policy interactions. As a result, optimal policy regimes may diverge not only across the union members, but also between the latter and the monetary union. In a two-country micro-founded New-Keynesian model for a monetary union, we consider two fiscal policy scenarios: (i) lump-sum taxes are raised to fully finance the government budget and (ii) lump-sum taxes do not ensure balanced budgets in each period; therefore, fiscal and monetary policies are expected to impinge on debt sustainability. For several degrees of country-size asymmetry, we compute optimal discretionary and dynamic non-cooperative policy games and compare their stabilization performance using a union-wide welfare measure. We also assess whether these outcomes could be improved, for the monetary union, through institutional policy arrangements. We find that, in the presence of government indebtedness, monetary policy optimally deviates from macroeconomic to debt stabilization. We also find that policy cooperation is always welfare increasing for the monetary union as a whole; however, indebted large countries may strongly oppose to this arrangement in favour of fiscal leadership. In this case, delegation of monetary policy to a conservative central bank proves to be fruitful to improve the union’s welfare.

Quantificação da difusão na ressonância magnética da mama: ADC e Kurtosis

Mestrado em Radiações Aplicadas às Tecnologias da Saúde. Área de especialização: Ressonância Magnética

Stabilization constraints from different-average public debt levels in a Monetary Union with country-size asymmetry

In the sequence of the recent financial and economic crisis, the recent public debt accumulation is expected to hamper considerably business cycle stabilization, by enlarging the budgetary consequences of the shocks. This paper analyses how the average level of public debt in a monetary union shapes optimal discretionary fiscal and monetary stabilization policies and affects stabilization welfare. We use a two-country micro-founded New-Keynesian model, where a benevolent central bank and the fiscal authorities play discretionary policy games under different union-average debt-constrained scenarios. We find that high debt levels shift monetary policy assignment from inflation to debt stabilization, making cooperation welfare superior to noncooperation. Moreover, when average debt is too high, welfare moves directly (inversely) with debt-to-output ratios for the union and the large country (small country) under cooperation. However, under non-cooperation, higher average debt levels benefit only the large country.

Effective teaching and optimal experiences: possible link

ISME, Thessaloniki, 2012

An heuristic approach for optimal location of gas supply units in transportation system

The best places to locate the Gas Supply Units (GSUs) on a natural gas systems and their optimal allocation to loads are the key factors to organize an efficient upstream gas infrastructure. The number of GSUs and their optimal location in a gas network is a decision problem that can be formulated as a linear programming problem. Our emphasis is on the formulation and use of a suitable location model, reflecting real-world operations and constraints of a natural gas system. This paper presents a heuristic model, based on lagrangean approach, developed for finding the optimal GSUs location on a natural gas network, minimizing expenses and maximizing throughput and security of supply.The location model is applied to the Iberian high pressure natural gas network, a system modelised with 65 demand nodes. These nodes are linked by physical and virtual pipelines – road trucks with gas in liquefied form. The location model result shows the best places to locate, with the optimal demand allocation and the most economical gas transport mode: by pipeline or by road truck.

Optimal location of gas supply units in natural gas system network

Natural gas industry has been confronted with big challenges: great growth in demand, investments on new GSUs – gas supply units, and efficient technical system management. The right number of GSUs, their best location on networks and the optimal allocation to loads is a decision problem that can be formulated as a combinatorial programming problem, with the objective of minimizing system expenses. Our emphasis is on the formulation, interpretation and development of a solution algorithm that will analyze the trade-off between infrastructure investment expenditure and operating system costs. The location model was applied to a 12 node natural gas network, and its effectiveness was tested in five different operating scenarios.

An efficient method for optimal location and sizing of fixed and switched shunt capacitors in large distribution systems

This paper proposes a computationally efficient methodology for the optimal location and sizing of static and switched shunt capacitors in large distribution systems. The problem is formulated as the maximization of the savings produced by the reduction in energy losses and the avoided costs due to investment deferral in the expansion of the network. The proposed method selects the nodes to be compensated, as well as the optimal capacitor ratings and their operational characteristics, i.e. fixed or switched. After an appropriate linearization, the optimization problem was formulated as a large-scale mixed-integer linear problem, suitable for being solved by means of a widespread commercial package. Results of the proposed optimizing method are compared with another recent methodology reported in the literature using two test cases: a 15-bus and a 33-bus distribution network. For the both cases tested, the proposed methodology delivers better solutions indicated by higher loss savings, which are achieved with lower amounts of capacitive compensation. The proposed method has also been applied for compensating to an actual large distribution network served by AES-Venezuela in the metropolitan area of Caracas. A convergence time of about 4 seconds after 22298 iterations demonstrates the ability of the proposed methodology for efficiently handling large-scale compensation problems.

Transmission costs allocation based on optimal re-dispatch

Congestion management of transmission power systems has achieve high relevance in competitive environments, which require an adequate approach both in technical and economic terms. This paper proposes a new methodology for congestion management and transmission tariff determination in deregulated electricity markets. The congestion management methodology is based on a reformulated optimal power flow, whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the transactions resulting from market operation. The proposed transmission tariffs consider the physical impact caused by each market agents in the transmission network. The final tariff considers existing system costs and also costs due to the initial congestion situation and losses. This paper includes a case study for the 118 bus IEEE test case.

ANN based support for distributed energy resources scheduling in smart grids

The future scenarios for operation of smart grids are likely to include a large diversity of players, of different types and sizes. With control and decision making being decentralized over the network, intelligence should also be decentralized so that every player is able to play in the market environment. In the new context, aggregator players, enabling medium, small, and even micro size players to act in a competitive environment, will be very relevant. Virtual Power Players (VPP) and single players must optimize their energy resource management in order to accomplish their goals. This is relatively easy to larger players, with financial means to have access to adequate decision support tools, to support decision making concerning their optimal resource schedule. However, the smaller players have difficulties in accessing this kind of tools. So, it is required that these smaller players can be offered alternative methods to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), intended to support smaller players’ resource scheduling. The used methodology uses a training set that is built using the energy resource scheduling solutions obtained with a reference optimization methodology, a mixed-integer non-linear programming (MINLP) in this case. The trained network is able to achieve good schedule results requiring modest computational means.

Caminhamento fotogramétrico com arranjo triangular de câmaras fotográficas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optimization techniques for power distribution planning with uncertainties: a comparative study

Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Quality of life, life satisfaction and happiness in shift- and non-shiftworkers

OBJECTIVE: To investigate the quality of life, life satisfaction, happiness and demands of work in workers with different work schedules. METHODS: The survey was carried out on professional workers in social care. Some were shiftworkers whose schedule included night shifts (N=311), some were shiftworkers without night shifts (N=207) and some were non-shiftworkers (N=1,210). Surveys were mailed and the response rate was 86%. For the purpose of this study several variables were selected from the Survey: The Quality of Life Profile, which measures importance, satisfaction, control and opportunities in nine domains of life plus measures of happiness, life satisfaction and demands of work. RESULTS: While both groups of shiftworkers, compared to non-shiftworkers, reported needing more physical effort to complete their work, and reported 'being' more physically tired, no differences were found in reports of overall happiness, life satisfaction or total quality of life. However, night-shiftworkers reported greater percentage of time unhappy than the other two groups of workers. In analyses of the quality of life, night-shiftworkers were less satisfied with domains of spiritual 'being' and physical and community 'belonging' than day-shiftworkers and non-shiftworkers. They also reported having fewer opportunities to improve their physical 'being', leisure, and personal growth than the other two groups. CONCLUSIONS: Quality of life in specific domains in night-shiftworkers was rated worse than in other groups of workers. Domain-based quality of life assessment gives more information regarding the particular needs of workers than overall or global measures of well-being.

Optimal methodology for renewable energy dispatching in islanded operation

The management of energy resources for islanded operation is of crucial importance for the successful use of renewable energy sources. A Virtual Power Producer (VPP) can optimally operate the resources taking into account the maintenance, operation and load control considering all the involved cost. This paper presents the methodology approach to formulate and solve the problem of determining the optimal resource allocation applied to a real case study in Budapest Tech’s. The problem is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The problem has also been solved by Evolutionary Particle Swarm Optimization (EPSO). The obtained results are presented and compared.