This paper introduces bupaR which is a collection of Rpackages which can be used for exploring and visualizing event data and monitoring processes. It creates a bridge between the BPM community and the broader R and data science communities. Furthermore, it stimulates the use of process mining in corporations, as R is a very wide used analysis tool in business, with its popularity still strongl...

The Infrared Data Association’s (IrDA) infrared data transmission protocol is a widely used mechanism for short-range wireless data communications. In order to provide flexibility for connections between devices of potentially disparate capabilities, IrDA devices negotiate the values of several transmission parameters based on the capabilities of the devices establishing the connection. This pa...

The concept of Banded pattern mining is concerned with the identification of “bandings” within zero-one data. A zero-one data set is said to be fully banded if all the “ones” can be arranged along the leading diagonal. The discovery of a banded pattern is of interest in its own right, at least in a data analysis context, because it tells us something about the data. Banding has also been shown ...

In this paper we propose a novel algorithm that provides bounded approximate solutions for decentralised coordination problems. Our approach removes cycles in any general constraint network by eliminating dependencies between functions and variables which have the least impact on the solution quality. It uses the max-sum algorithm to optimally solve the resulting tree structured constraint netw...

suspended sediment estimation is an important factor from different aspects including, farming, soil conservation, dams, aquatic life, as well as various aspects of the research. there are different methods for suspended sediment estimation. this study aims to estimate suspended sediment using feed forward neural network with error back propagation with levenberg-marquardt back propagation algo...

in this paper, we present an application of evolved neural networks using a real coded genetic algorithm for simulations of monthly groundwater levels in a coastal aquifer located in the shabestar plain, iran. after initializing the model with groundwater elevations observed at a given time, the developed hybrid genetic algorithm-back propagation (ga-bp) should be able to reproduce groundwater ...

Affinity propagation (AP) is a clustering method that can find data centers or clusters by sending messages between pairs of data points. Seed Affinity Propagation is a novel semisupervised text clustering algorithm which is based on AP. AP algorithm couldn’t cope up with part known data direct. Therefore, focusing on this issue a semi-supervised scheme called incremental affinity propagation c...

We propose an algorithm to compute the optimal parameters of a probabilistic data propagation algorithm for wireless sensor networks (WSN). The probabilistic data propagation algorithm we consider was introduced in previous work, and it is known that this algorithm, when used with adequate parameters, balances the energy consumption and increases the lifespan of the WSN. However, we show that i...

Mitigation of anomalous propagation clutter (AP) is an ongoing problem in radar meteorology. AP clutter routinely contaminates radar data masking weather returns causing poor data quality. The problem is typically mitigated by clutter filtering all radar data but this will also eliminate weather data at zero velocity. With the advent of fast digital receivers capable of real time spectral proce...