ROMANIAN HIGHER EDUCATION REFORM AND ADAPTATION BETWEEN THE REQUIREMENTS OF THE KNOWLEDGE SOCIETY

In today's society, characterized by a continuous process of globalization andknowledge-based economy, intellectual property is the central resource that creates the realvalue in all sectors of economic life. In this context, higher education's mission is to providethe highest quality standard representing a main actor in providing highly skilled workforceand creating knowledge. Thus, we say that to meet the new challenges that universities is needto go through the stages of a process of reform and adaptation, in line with the LisbonStrategy.Consequently, our approach is to put in the foreground the need to create a new system ofhigher education to meet the new demands of society.higher education quality reform, knowledge management education.

Data center virtualization and its economic implications for the companies

In the current situation of the economic crisis, when companies target budget cuttings in a context of an explosive data growth, the IT community must evaluate potential technology developments not only on their technical advantages, but on their economic effects as well.data centre; virtualization; tiered storage; provisioning software; unified computing.

DECISION SUPPORT IN CAR LEASING: A FORECASTING MODEL FOR RESIDUAL VALUE ESTIMATION

The paper proposes a methodology to support pricing decisions in the car leasing industry. In particular, the price is given by the monthly fee to be paid by the lessee as compensation for using a car over some contract horizon. After contract expiration, lessors are obliged to take back the vehicle, which will then be sold in the used car market. Therefore, lessors require an accurate estimate of cars’ residual values to manage the risk inherent to their business and determine profitable prices. We explore the organizational and technical requirements associated with this forecasting task and develop a prediction model that complies with identified application constraints. The model is rigorously tested within an empirical study and compared to established benchmarks. The results obtained in several experiments provide strong evidence for the proposed model being effective in generating accurate predictions of cars’ residual values and efficient in requiring little user intervention

«E-SCIENTROCHAIR»- ONLINE DATABASE FOR MANAGEMENT AND ASSESSMENT OF THE RESEARCH RESOURCES OF THE UNIVERSITY BASIS UNIT – THE CHAIR

The concept named e-ScientRoChair proposes searching for new informing and documentation opportunities, on fundamental structure in academic scientific research, meaning the chair or the research team, anabling the possibility to publish and as well as toOnline Database, Chair, Scientific Exchange, Scientific Research Components

Bayesian Measurement Error Correction in Structured Additive Distributional Regression with an Application to the Analysis of Sensor Data on Soil-Plant Variability

The flexibility of the Bayesian approach to account for covariates with measurement error is combined with semiparametric regression models for a class of continuous, discrete and mixed univariate response distributions with potentially all parameters depending on a structured additive predictor. Markov chain Monte Carlo enables a modular and numerically efficient implementation of Bayesian measurement error correction based on the imputation of unobserved error-free covariate values. We allow for very general measurement errors, including correlated replicates with heterogeneous variances. The proposal is first assessed by a simulation trial, then it is applied to the assessment of a soil-plant relationship crucial for implementing efficient agricultural management practices. Observations on multi-depth soil information forage ground-cover for a seven hectares Alfalfa stand in South Italy were obtained using sensors with very refined spatial resolution. Estimating a functional relation between ground-cover and soil with these data involves addressing issues linked to the spatial and temporal misalignment and the large data size. We propose a preliminary spatial interpolation on a lattice covering the field and subsequent analysis by a structured additive distributional regression model accounting for measurement error in the soil covariate. Results are interpreted and commented in connection to possible Alfalfa management strategies

Data center virtualization and its economic implications for the companies

In the current situation of the economic crisis, when companies target budgetcuttings in a context of an explosive data growth, the IT community must evaluate potentialtechnology developments not only on their technical advantages, but on their economiceffects as well. More then ever, the old cliché “doing more things with fewer resources” istrue today. Many IT companies started building very large facilities, called data centers(DCs) or Internet DC (IDCs), which provide businesses a wide range of solutions forsystems deployment and operation. In recent years, the IT departments around the worldhave moved from data center and infrastructure consolidation to virtualization.Data center virtualization is the process of aligning available resources with the actualneeds of the offered services, moving from physical servers to virtual servers, sharing andprovisioning servers, networks, storage, and applications. By taking advantage of threebasic innovations — virtualization, tiered storage architectures and dynamic provisioningsoftware — an organization can achieve greater efficiencies in their current computingenvironment.Such a unified computing architecture offers end-to-end virtualization; all structures areoptimized for virtualized environments, from the CPU to the aggregation layer. Incombination with embedded management, this new approach increases responsiveness andreduces the opportunities for human error, improving consistency and reducing server andnetwork deployment times

An Almgren monotonicity formula for discrete harmonic functions

The celebrated Almgren monotonicity formula for harmonic functions $u:\mathbb{R}^n \rightarrow \mathbb{R}$ says that its $L^2-$energy concentrated on a sphere of radius $r$, when measured in a suitable sense, is non-decreasing: if $u$ oscillates at a certain scale, it has even larger oscillations at a larger scale. We prove a discrete analogue of the Almgren monotonicity formula for harmonic functions on infinite combinatorial graphs $G=(V,E)$. Some applications are discussed