Data sets of spatially irregular meteorological observations interpolated to a regular grid are not only important for climate analyses but are also essential in order to derive climatologies for rainfall-runoff models which require meteorological data sets as input forcing. For example, in the...

Over the past three years Italy has witnessed a rapid growth in the photovoltaic energy market, followed by an equally sudden decline when the government decided to reduce the incentives. This sharp change in the trend of the market calls into question the achievement of Grid Parity and the...

This study describes a method for programming a plug-in electric vehicle agent that can be used in power system models and in embedded systems implemented in real plug-in electric vehicles. Implementing the software in real-life applications and in simulation tools enables research with a high...

We implement a dynamic programming algorithm on a computational grid consisting of loosely coupled processors, possibly including clusters and individual workstations. The grid changes dynamically during the computation, as processors enter and leave the pool of workstations. The algorithm is...

We present the design of a service oriented architecture which facilitates flexible managerial decision making in dynamic business networks. We have implemented and tested this architecture in the MinneTAC trading agent, which is designed to compete in the Trading Agent Competition for Supply...

The article responds to a grid created by Leonard Riskin to describe mediator orientations. As Riskin’s Grid indicates, many mediators in practice evaluate the fair or likely court outcome when necessary to move forward on a particular issue or on the entire dispute. While this article...

Big data analytics and deep learning are nowadays two of the most active research areas in computer science. As the data is becoming bigger and bigger, deep learning has a very important role to play in data analytics, and big data technologies will give it huge opportunities for different...

In numerous solutions, the distributed stochastic gradient descent algorithm is one of the most popular algorithms for parallelization matrix decomposition. However, in parallel calculation, the computing speed of each computing node was greatly different because of the imbalance of the...