The economical decision and the management of risk

The decision process as we know it today is influenced by many factors, especially by the important changes that appear in the economical environment. A good decision can be taken only after analyzing all available data and information, but, at the same time, after identifying and, if possible, reducing the influence of any possible risks that may appear. In this article, we refer to some aspects of the decision and the decision process and, in the second part, to elements regarding risk management.decision, risk management

MODELS FOR LABOR FORCE ANALYSIS

Economic policy measures are generally fundamented on a system of indicators which allows both a static and a dynamic analysis of the complex processes taking place at macroeconomic level, especially when dealing with structural changes or dependences between population and economy. Labor market development and functioning is one of the key issues of Romania’s transition to the market economy. This requires the total reconsideration of the employment policy and of the use of labor in general, as well as of the mechanisms regulating demand and supply of labor.labor force indicators, unemployment rate, employment indicators

Technical Report: A Trace-Based Performance Study of Autoscaling Workloads of Workflows in Datacenters

To improve customer experience, datacenter operators offer support for simplifying application and resource management. For example, running workloads of workflows on behalf of customers is desirable, but requires increasingly more sophisticated autoscaling policies, that is, policies that dynamically provision resources for the customer. Although selecting and tuning autoscaling policies is a challenging task for datacenter operators, so far relatively few studies investigate the performance of autoscaling for workloads of workflows. Complementing previous knowledge, in this work we propose the first comprehensive performance study in the field. Using trace-based simulation, we compare state-of-the-art autoscaling policies across multiple application domains, workload arrival patterns (e.g., burstiness), and system utilization levels. We further investigate the interplay between autoscaling and regular allocation policies, and the complexity cost of autoscaling. Our quantitative study focuses not only on traditional performance metrics and on state-of-the-art elasticity metrics, but also on time- and memory-related autoscaling-complexity metrics. Our main results give strong and quantitative evidence about previously unreported operational behavior, for example, that autoscaling policies perform differently across application domains and by how much they differ.Comment: Technical Report for the CCGrid 2018 submission "A Trace-Based Performance Study of Autoscaling Workloads of Workflows in Datacenters

Second order adjoints for solving PDE-constrained optimization problems

Inverse problems are of utmost importance in many fields of science and engineering. In the variational approach inverse problems are formulated as PDE-constrained optimization problems, where the optimal estimate of the uncertain parameters is the minimizer of a certain cost functional subject to the constraints posed by the model equations. The numerical solution of such optimization problems requires the computation of derivatives of the model output with respect to model parameters. The first order derivatives of a cost functional (defined on the model output) with respect to a large number of model parameters can be calculated efficiently through first order adjoint sensitivity analysis. Second order adjoint models give second derivative information in the form of matrix-vector products between the Hessian of the cost functional and user defined vectors. Traditionally, the construction of second order derivatives for large scale models has been considered too costly. Consequently, data assimilation applications employ optimization algorithms that use only first order derivative information, like nonlinear conjugate gradients and quasi-Newton methods. In this paper we discuss the mathematical foundations of second order adjoint sensitivity analysis and show that it provides an efficient approach to obtain Hessian-vector products. We study the benefits of using of second order information in the numerical optimization process for data assimilation applications. The numerical studies are performed in a twin experiment setting with a two-dimensional shallow water model. Different scenarios are considered with different discretization approaches, observation sets, and noise levels. Optimization algorithms that employ second order derivatives are tested against widely used methods that require only first order derivatives. Conclusions are drawn regarding the potential benefits and the limitations of using high-order information in large scale data assimilation problems

Effects of “classical” vs. “dynamic” silviculture of sessile oak-dominated stands in terms of height, diameter increments and natural mortality

Traditional oak silviculture in Romania is associated with high labor costs and long rotation cycles which are imposed by current norms and regulations. A small-scale R&D project, consisting of a block with four plots of 200 m2, was established in 2001 in a 15-year old sessile oak-dominated stand. The stand was regenerated naturally through the application of group shelterwood cutting. In each plot, ”potential” final crop trees were selected based on vigor-quality-distribution criteria and marked with paint. Silvicultural interventions like cleaning-respacing and thinning of different intensities were performed in three plots (the fourth one was kept as control) in 2001, 2004 and 2009. The effect of stand density on diameter increment was more obvious when considering only the “potential” final crop trees than when all trees were considered. Their quadratic mean diameter (QMD) had reached values close to 20 cm at 35 (30-40) years in the plots with the lowest stand density (STT) and about 15-16 cm for other plots. STT stand with the lowest stand density shows low HDR values having slander trees. The mortality intensity between 2001 and 2019 was highest in the control plot and lowest in STT. Sessile oak showed the highest mortality, followed by Hungarian oak and Turkey oak. In all plots, trees had reached heights corresponding to the hg of ca. 15 m, which is normal for a sessile oak stand of high productivity. The obtained results indicate the ”dynamic”, crop tree silviculture with the active selection of the most valuable individuals as ”potential” final crop trees at the end of thicket stage as being a possible solution for managing sessile oak young and medium-aged stands. Nonetheless, these trees should be managed by subsequent crown thinning, in order to produce timber with as uniform as possible radial increments of 2-3 mm, as is requested by veneer and high-quality saw log buyers

The coming decade of digital brain research - A vision for neuroscience at the intersection of technology and computing

Brain research has in recent years indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modeling at multiple scales – from molecules to the whole system. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain integrates high-quality basic research, systematic data integration across multiple scales, a new culture of large-scale collaboration and translation into applications. A systematic approach, as pioneered in Europe’s Human Brain Project (HBP), will be essential in meeting the pressing medical and technological challenges of the coming decade. The aims of this paper are: To develop a concept for the coming decade of digital brain research To discuss it with the research community at large, with the aim of identifying points of convergence and common goals. To provide a scientific framework for current and future development of EBRAINS. To inform and engage stakeholders, funding organizations and research institutions regarding future digital brain research. To identify and address key ethical and societal issues. While we do not claim that there is a ‘one size fits all’ approach to addressing these aspects, we are convinced that discussions around the theme of digital brain research will help drive progress in the broader field of neuroscience

THE ROLE OF AN INTEGRATED E-LEARNING PLATFORM IN INCREASING THE PROCESSMANAGEMENT EFFICIENCY

This paper aims to present the steps taken and solutions implemented at the Cisco Networking Academy of the University of Bucharest in order to increase the process-management efficiency and the student satisfaction degree, mainly via the implementation of an own e-learning learning platform.The results are a significant improvement of work relationships, due to the fact that everyone's responsibilities are clearly defined together with the expectations for each employee. Furthermore, productivity tools enable us and our instructors to concentrate on increasing the quality of our students' learning experience in order to obtain even higher degrees of student satisfaction, retention, and promovability as a direct measure of teaching/learning success.Instructor Experience, User satisfaction, E-learning platform, Management Module, Student Assessment

Implicación del patrón respiratorio en pacientes obesos intervenidos de cirugía bariátrica

La obesidad es una patología que cada vez tiene una incidencia más alta en la población, y en el abordaje terapéutico se contempla la posibilidad de la cirugía bariátrica. Los pacientes obesos desarrollan complicaciones respiratorias, algunas de manera regular, llegando a afectar a más del 50%. El empleo de fisioterapia respiratoria pre y postquirúrgica disminuye la incidencia de estas complicaciones y reduce el tiempo de estancia hospitalaria. En esta revisión bibliográfica se analizan las implicaciones del patrón respiratorio en pacientes intervenidos de cirugía bariátrica.Grado en Enfermerí