The efforts of the European Union (EU) in energy supply domain aim to introduce intelligent grid management across whole EU.The target is planned contain 80% all meters be smart generating data every 15 minutes.Thus, EU will grow rapidly very near future.Smart are successively installed a phased roll-out, and first meter samples ready for different types analysis order understand data, make precise predictions support control.In this paper, we propose an incremental heterogeneous ensemble...

Short tandem repeats (STRs) are regions of a genome containing many consecutive copies the same short motif, possibly with small variations. Analysis STRs has clinical uses but is limited by technology mainly due to surpassing used read length. Nanopore sequencing, as one long-read sequencing technologies, produces very long reads, thus offering more possibilities study and analyze STRs. Basecalling nanopore reads however particularly unreliable in repeating regions, therefore direct...

In this paper we study different parallel implementations of the Savings based Ant System algorithm developed for solving Vehicle Routing Problem. We analyze effects low-level parallelization, multiple search strategies and domain decomposition approaches. For speedup efficiency as well solution quality are reported. Different information exchanges analyzed within strategies.

Ensuring sustainability demands more precise energy management to minimize wastage. With the deployment of smart grids that provide a huge amount data, new methods machine learning come light ensure predictions. deep which require are starting show promise with increasing accuracy. In this paper, we present methodology for predicting time series uses Deep Neural Networks, specifically Long Short-Term Memory (LSTM) algorithm Sequence (S2S) architecture. We improve prediction accuracy, when...

The paper presents an improvement of incremental adaptive power load forecasting methods by performing cluster analysis prior to forecasts. For clustering the centroid based method K-means, with K-means++ centroids initialization, was used. Ten various were compared in order find most suitable ones combine clustering. used data set comes from Ireland, where half-hourly measurements electricity consumption more than 3600 households during two years at disposal. We have tested types...

Abstract We present a general optimization technique for the three-dimensional finite-difference (FD) modeling of seismic-wave propagation and earthquake ground motion. Our combined memory (CDMO) naturally comprises core disk optimization. While is based on keeping only limited number model planes in at given time, data compression wavelet domain. CDMO enables significant reduction both computer requirements. general: It applicable to any explicit scheme conventional or staggered grid....

Abstract This paper presents a new method for forecasting load of individual electricity consumers using smart grid data and clustering. The from all are used clustering to create more suitable training sets methods. Before clustering, time series efficiently preprocessed by normalisation the computation various model-based representation Final centroid-based forecasts scaled saved parameters forecast every consumer. Our is compared with approach that creates consumer separately. Evaluation...

This paper presents a new method for forecasting the load of individual electricity consumers using smart grid data and clustering. The from all are used clustering to create more suitable training sets methods. Before clustering, time series efficiently preprocessed by normalisation computation representations multiple linear regression model. Final centroid-based forecasts scaled saved parameters forecast every consumer. Our is compared with approach that creates consumer separately....

The complexity of certain problems causes that classical methods for finding exact solutions have some limitations. In this paper we propose an incremental heterogeneous ensemble model time series prediction where biologically inspired algorithms

In this paper we study behaviour of Ant Colony Optimization algorithm for solving the Vehicle Routing Problem implemented by POSIX Threads in parallel cluster environment. The is based on a fine-grained parallelism strategy which uses asynchronous communication cooperation finding solutions. Our aim to analyze effect proposed method speedup, execution and time with respect quality solution.

Computing similarity between 2 nucleotide sequences is one of the fundamental problems in bioinformatics. Current methods are based mainly on major approaches: (1) sequence alignment, which computationally expensive, and (2) faster, but less accurate, alignment-free various statistical summaries, for example, short word counts. We propose a new distance measure mathematical transforms from domain signal processing. To tolerate large-scale rearrangements sequences, transform computed across...

Detection of epistatic interactions associated with diseases can improve prevention and diagnosis those diseases. Epistatic are nonlinear interaction effects single nucleotide polymorphisms (SNPs), which substitution mutations occurring at some specific position in the genome. Detecting associations between them is very computationally expensive, as more complex be only two SNPs, thus making a large quantity possible SNP combinations needed to test. To cope such high computational...

Abstract Motivation Short tandem repeats (STRs) are regions of a genome containing many consecutive copies the same short motif, possibly with small variations. Analysis STRs has clinical uses, but is limited by technology mainly due to surpassing used read length. Nanopore sequencing, as one long sequencing technologies, produces very reads, thus offering more possibilities study and analyze STRs. Basecalling nanopore reads however particularly unreliable in repeating regions, therefore...

Many practical problems, such as portfolio management, problems in manufacturing, transportation or power generation, can be modeled stochastic programs. Stochastic programs provide an effective framework for sequential decision with uncertain data, when uncertainty by a discrete set of scenarios. In this paper we present algorithm solving three-stage linear program based on the Birge and Qi factorization constraint matrix product frame primal-dual path-following interior point method....