Search results for "Memory."
showing 10 items of 1949 documents
kmcEx: memory-frugal and retrieval-efficient encoding of counted k-mers.
2018
Abstract Motivation K-mers along with their frequency have served as an elementary building block for error correction, repeat detection, multiple sequence alignment, genome assembly, etc., attracting intensive studies in k-mer counting. However, the output of k-mer counters itself is large; very often, it is too large to fit into main memory, leading to highly narrowed usability. Results We introduce a novel idea of encoding k-mers as well as their frequency, achieving good memory saving and retrieval efficiency. Specifically, we propose a Bloom filter-like data structure to encode counted k-mers by coupled-bit arrays—one for k-mer representation and the other for frequency encoding. Exper…
Juggler's exclusion process
2012
Juggler's exclusion process describes a system of particles on the positive integers where particles drift down to zero at unit speed. After a particle hits zero, it jumps into a randomly chosen unoccupied site. We model the system as a set-valued Markov process and show that the process is ergodic if the family of jump height distributions is uniformly integrable. In a special case where the particles jump according to a set-avoiding memoryless distribution, the process reaches its equilibrium in finite nonrandom time, and the equilibrium distribution can be represented as a Gibbs measure conforming to a linear gravitational potential.
Anomalous diffusion and nonlinear relaxation phenomena in stochastic models of interdisciplinary physics
2020
The study of nonlinear dynamical systems in the presence of both Gaussian and non-Gaussian noise sources is the topic of this research work. In particular, after shortly present new theoretical results for statistical characteristics in the framework of Markovian theory, we analyse four different physical systems in the presence of Levy noise source. (a) The residence time problem of a particle subject to a non-Gaussian noise source in arbitrary potential profile was analyzed and the exact analytical results for the statistical characteristics of the residence time for anomalous diffusion in the form of Levy flights in fully unstable potential profile was obtained. Noise enhanced stability …
Stereotype Threat Effect on a Simple Motor Task: An Investigation of the Visuo-Spatial Working Memory
2020
Purpose: Based on the Chalabaev et al. (2013) study showing that in a Stereotype Threat (ST) situation the velocity of force production in a simple motor task can be affected, this study aimed to r...
Strain-Controlled Giant Magnetoresistance in Spin Valves Grown on Shape Memory Alloys
2019
We report a strain-mediated giant magnetoresistance (GMR) in spin valves (SPVs) grown on shape memory alloys (SMAs). The SPVs with a stacking structure of Al2O3/Co90Fe10/Cu/Co90Fe10/IrMn/Pt were de...
Are Neural Networks Imitations of Mind?
2015
Artificial neural networks are often understood as a good way to imitate mind through the web structure of neurons in brain, but the very high complexity of human brain prevents to consider neural networks as good models for human mind;anyway neural networks are good devices for computation in parallel. The difference between feed-forward and feedback neural networks is introduced; the Hopfield network and the multi-layers Perceptron are discussed. In a very weak isomorphism (not similitude) between brain and neural networks, an artificial form of short term memory and of acknowledgement, in Elman neural networks, is proposed.
Firefly algorithm based upon slicing structure encoding for unequal facility layout problem
2019
Finding the locations of departments or machines in a workspace is classified as a Facility Layout Problem. Good placement of departments has a relevant influence on manufacturing costs, work in process, lead times and production efficiency. This paper analyses the problem of allocating departments with restrictions in terms of unequal area and rectangular shape within a facility, in order to minimize the sum of material handling costs taking into account the satisfaction of the aspect ratio requested. In particular, we propose for the first time a Firefly Algorithm based on the slicing structure encoding. The proposed method was tested comparing the results obtained from other authors on t…
A multi objective genetic algorithm for the facility layout problem based upon slicing structure encoding
2012
This paper proposes a new multi objective genetic algorithm (MOGA) for solving unequal area facility layout problems (UA-FLPs). The genetic algorithm suggested is based upon the slicing structure where the relative locations of the facilities on the floor are represented by a location matrix encoded in two chromosomes. A block layout is constructed by partitioning the floor into a set of rectangular blocks using guillotine cuts satisfying the areas requirements of the departments. The procedure takes into account four objective functions (material handling costs, aspect ratio, closeness and distance requests) by means of a Pareto based evolutionary approach. The main advantage of the propos…
Explorations of familiarity produced by words with specific combinations of letters
2010
We explore familiarity-based recognition using a paradigm devised by Parkin et al. (2001). The task consists of the creation of two lists of words written with one of two different subsets of letters of the alphabet. We manipulated study time (50, 100, 200, 500 ms per word) of words with different letter probabilistic structure to those originally used by Parkin et al. Letter-based familiarity responding was robust and present even at rates producing otherwise chance performance. A second experi- ment and structural equation modelling led us to interpret the results from the point of view of a theory that takes into account the processing of similarities and differences (Hunt & MacDaniel, (…
Including invariances in SVM remote sensing image classification
2012
This paper introduces a simple method to include invariances in support vector machine (SVM) for remote sensing image classification. We rely on the concept of virtual support vectors, by which the SVM is trained with both the selected support vectors and synthetic examples encoding the invariance of interest. The algorithm is very simple and effective, as demonstrated in two particularly interesting examples: invariance to the presence of shadows and to rotations in patchbased image segmentation. The improved accuracy (around +6% both in OA and Cohen's κ statistic), along with the simplicity of the approach encourage its use and extension to encode other invariances and other remote sensin…