Abstract
Multicore processors are available for over a decade, but general purpose database management systems (DBMS) still cannot fully explore the computational resources of these platforms. This paper explores a simple and easy to deploy approach for improving DBMS performance in multicore platforms, by maintaining multiple database engines running in parallel, rather than a single instance, thus circumventing the increase in contention due to load interactions. Unlike previous works, we focus on in-memory DBMS, exploring different design solutions that combine distributed systems and concurrent programming techniques. We show that we are able to improve performance over standalone solutions, without modifying either database or application code, by up to 3 times while minimizing response times.

Abstract
Power systems with high wind penetration experience increased variability and uncertainty, such that determination of the required additional operating reserve is attracting a significant amount of attention and research. This paper presents methods used in recent wind integration analyses and operating practice, with key results that compare different methods or data. Wind integration analysis over the past several years has shown that wind variability need not be seen as a contingency event. The impact of wind will be seen in the reserves for non-event operation (normal operation dealing with deviations from schedules). Wind power will also result in some events of larger variability and large forecast errors that could be categorized as slow events. The level of operating reserve that is induced by wind is not constant during all hours of the year, so that dynamic allocation of reserves will reduce the amount of reserves needed in the system for most hours. The paper concludes with recent emerging trends.

Abstract
Laser-guide-star multiconjugate adaptive optics (MCAO) systems require natural guide stars (NGS) to measure tilt and tilt-anisoplanatism modes. Making optimal use of the limited number of photons coming from such, generally dim, sources is mandatory to obtain reasonable sky coverage, i.e., the probability of finding asterisms amenable to NGS wavefront (WF) sensing for a predefined WF error budget. This paper presents a Strehl-optimal (minimum residual variance) spatiotemporal reconstructor merging principles of modal atmospheric tomography and optimal stochastic control theory. Simulations of NFIRAOS, the first light MCAO system for the thirty-meter telescope, using ~500 typical NGS asterisms, show that the minimum-variance (MV) controller delivers outstanding results, in particular for cases with relatively dim stars (down to magnitude 22 in the H-band), for which lowtemporal frame rates (as low as 16 Hz) are required to integrate enough flux. Over all the cases tested ~21 nm rms median improvement in WF error can be achieved with the MV compared to the current baseline, a type-II controller based on a double integrator. This means that for a given level of tolerable residual WF error, the sky coverage is increased by roughly 10%, a quite significant figure. The improvement goes up to more than 20% when compared with a traditional single-integrator controller. © 2013 Optical Society of America.

Abstract
Programs increasingly rely on the use of complex component libraries, such as in-memory databases. As any other software, these libraries have bugs that may lead to the application failure. In this work we revisit the idea of software component replication for masking software bugs in the context of multi-core systems. We propose a new abstraction: a Macro-Component. A Macro-Component is a software component that includes several internal replicas with diverse implementations to detect and mask bugs. By relying on modern multicores processing capacity it is possible to execute the same operation in multiple replicas concurrently, thus incurring in minimal overhead. Also, by exploring the multiple existent implementations of well-known interfaces, it is possible to use the idea without incurring in additional development cost. © 2013 Springer-Verlag.

Abstract
With the development of synchronized phasor measurement technology in recent years, it gains great interest the use of PMU measurements to improve state estimation performances due to their synchronized characteristics and high data transmission speedThe ability of the Phasor Measurement Units (PMU) to directly measure the system state is a key over SCADA measurement system. PMU measurements are superior to the conventional SCADA measurements in terms of resolution and accuracy. Since the majority of measurements in existing estimators are from conventional SCADA measurement system, it is hard to be fully replaced by PMUs in the near future so state estimators including both phasor and conventional SCADA measurements are being consideredIn this paper, a mixed measurement (SCADA and PMU measurements) state estimator is proposedSeveral useful measures for evaluating various aspects of the performance of the mixed measurement state estimator are proposed and explainedState Estimator validity, performance and characteristics of the results on IEEE 14 bus test system and IEEE 30 bus test system are presented. © ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING.

Abstract
PhenoSat is an experimental software tool that produces phenological information from satellite vegetation index time series. The main characteristics and functionalities of the PhenoSat tool are presented, and its performance is compared against observed measures and other available software applications. A multiyear experiment was carried out for different vegetation types: vineyard, low shrublands, and seminatural meadows. Temporal satellite normalized difference vegetation index (NDVI) data provided by MODerate resolution Imaging Spectroradiometer and Satellite Pour l'Observation de la Terre VEGETATION were used to test the ability of the software in extracting vegetation dynamics information. Three important PhenoSat features were analyzed: extraction of the main growing season information, estimation of double growth season parameters, and the advantage of selecting a temporal region of interest. Seven noise reduction filters were applied: cubic smoothing splines, polynomial curve fitting, Fourier series, Gaussian models, piecewise logistic, Savitzky-Golay (SG), and a combination of the last two. The results showed that PhenoSat is a useful tool to extract NDVI metrics related to vegetation dynamics, obtaining high significant correlations between observed and estimated parameters for most of the phenological stages and vegetation types studied. Using the combination of SG and piecewise logistic to fit the NDVI time series, PhenoSat obtained correlations higher than 0.71, except for the seminatural meadow start of season. The selection of a temporal region of interest improved the fitting process, consequently providing more reliable phenological information.