In order to overcome some of the inherent pessimism of traditional static analysis, we propose a method for parametric WCET analysis expressing the WorstCase Execution Time (WCET) of a program as an expression in terms of the input data of a program. Besides giving more information about the execution time behaviour of the program, this also has benefits in component based development where reu...

Traditional Meta-Learning requires long training times, and is often focused on optimizing performance quality, neglecting computational complexity. Algorithm Portfolios are more robust, but present similar limitations. We reformulate algorithm selection as a time allocation problem: all candidate algorithms are run in parallel, and their relative priorities are continually updated based on run...

The massive parallelism and faster random memory access of Graphics Processing Units (GPUs) promise to further accelerate complex analytics operations such as joins and grouping, but also provide additional challenges to optimizing their performance. There are more implementation alternatives to consider on the GPU, such as exploiting different types of memory on the device and the division of ...

The paper presents a DEM model for simulating dry granular avalanche down an incline. Flow pattern and impact forces on rigid obstacles are considered. Results of the simulations are compared with experimental data reported in the literature. The experiments include granular flow along an inclined channel and three-dimensional free surface flow on an inclined chute merging into a horizontal run...

In this paper, we propose a parametric model checking algorithm for a subclass of Timed Automata called Parametric Time-Interval Automata(PTIA). In a PTIA, we can specify upperand lower-bounds of the execution time (time-interval) of each transition using parameter variables. The proposed algorithm takes two inputs, a model described in a PTIA and a property described in a PTIA accepting all in...

This paper deals with discrete-time Markov control processes in Borel spaces, with unbounded rewards. The criterion to be optimized is a long-run samplepath (or pathwise) average reward subject to constraints on a long-run pathwise average cost. To study this pathwise problem, we give conditions for the existence of optimal policies for the problem with “expected” constraints. Moreover, we show...

This paper explores single-equation nonlinear error correction (NEC) models with linear and nonlinear cointegrated variables. Within the class of semiparametric NEC models, we use smoothing splines. Within the class of parametric models, we discuss the interesting properties of cubic polynomial NEC models and we show how they can be used to identify unknown threshold points in asymmetric models...

The Burr type XII has been studied for various applications of lifetime modelings. However, control charts related to the Burr type XII percentiles have not been seen in the literature. In this paper, three control charts for the Burr type XII percentiles are investigated. An extensive Monte Carlo simulation study is conducted to compare among the Shewhart-type chart, and parametric bootstrap c...

This paper discusses parametric, nonparametric, and semiparametric models of urban growth. To illustrate differences across approaches, we test Gibrat's law in the long run, using three methods different datasets: Spanish capital cities regions (1900–2011, annual data) US MSAs (1900–2000, decennial data). Our results reveal that estimation relationship between growth initial size can significan...