Preprints (not yet peer-reviewed)

50 downloads
492 views

The nonparametric minimum hypergeometric (mHG) test is a popular alternative to Kolmogorov-Smirnov (KS)-type tests for determining gene set enrichment. However, these approaches have not been compared to each other in a quantitative manner. Here, I first perform...

["Computational Biology","Algorithms and Analysis of Algorithms","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.1962v3
13 downloads
22 views

Recognition of human emotions from the imaging templates is useful in a wide variety of human-computer interaction and intelligent systems applications. However, the automatic recognition of facial expressions using image template matching techniques suffer from...

["Human-Computer Interaction","Algorithms and Analysis of Algorithms","Artificial Intelligence","Computer Vision","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.2794v1
10 downloads
150 views

Motivated by the increasing amount of voices who ask for careful consideration of what context-rich data analysis methods can tell us about the activities of human collectives, we contribute an argumentation that employs a dialectic of literature on the philosophy...

["Data Mining and Machine Learning","Data Science","Network Science and Online Social Networks","Social Computing","World Wide Web and Web Science"]
doi:10.7287/peerj.preprints.2789v1
29 downloads
124 views

Background. The availability of large databases containing high resolution three-dimensional (3D) models of proteins in conjunction with functional annotation allows the exploitation of advanced supervised machine learning techniques for automatic protein function...

["Bioinformatics","Computational Biology","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.2778v1
16 downloads
35 views

Feature selection in machine learning is of great interest since it is reckoned as creating more efficient predictive models in several engineering domains. It is even of special importance in the pulp and paper transformation industry as the knowledge of this...

["Artificial Intelligence","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.2749v1
27 downloads
94 views

Flight simulators are systems composed of numerous off-the-shelf components that allow pilots and maintenance crew to prepare for common and emergency flight procedures for a given aircraft model. A simulator must follow severe safety specifications to guarantee...

["Data Mining and Machine Learning","Scientific Computing and Simulation","Software Engineering"]
doi:10.7287/peerj.preprints.2670v1
8 downloads
63 views

Data mining is one of the main activities in bioinformatics, specifically to extract knowledge from massive data sets related with gene expression measurement, CNV, DNA strings, and others. A long array of methods are used to perform such task, ranging from the...

["Bioinformatics","Computational Biology","Algorithms and Analysis of Algorithms","Data Mining and Machine Learning","Optimization Theory and Computation"]
doi:10.7287/peerj.preprints.2635v1
26 downloads
63 views

In this paper a method for detection of image forgery in lossy compressed digital images known as error level analysis (ELA) is presented and it's noisy components are filtered with automatic wavelet soft-thresholding. With ELA, a lossy compressed image is recompressed...

["Artificial Intelligence","Computer Vision","Data Mining and Machine Learning","Graphics"]
doi:10.7287/peerj.preprints.2619v1
71 downloads
202 views

Software forges like GitHub host millions of repositories. Software engineering researchers have been able to take advantage of such a large corpora of potential study subjects with the help of tools like GHTorrent and Boa. However, the simplicity in querying comes...

["Data Mining and Machine Learning","Software Engineering"]
doi:10.7287/peerj.preprints.2617v1
30 downloads
194 views

Sparse coding is an effective operating principle for the brain, one that can guide the discovery of features and support the learning of assocations. Here we show how spiking neurons with discrete dendrites can learn sparse codes via an online, nonlinear Hebbian...

["Computational Biology","Adaptive and Self-Organizing Systems","Artificial Intelligence","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.2595v1
38 downloads
218 views

New challenges in the efficient management of cities depend on a deep knowledge of their inner structures. It is therefore very important to have access to reliable models of cities characteristics and organization. This paper aims at providing and validating a...

["Data Mining and Machine Learning","Data Science","Graphics","Scientific Computing and Simulation","Spatial and Geographic Information Systems"]
doi:10.7287/peerj.preprints.2264v3
60 downloads
297 views

Natural hazards and land management issues can benefit nowadays from the increasing availability of free, high-resolution satellite imagery that opens the way to fine scale detailed investigations. In high elevation catchments the analysis of vegetation dynamics...

["Data Mining and Machine Learning","Spatial and Geographic Information Systems"]
doi:10.7287/peerj.preprints.2269v2
109 downloads
568 views

Floods are frequent and widespread in Italy and pose a severe risk for the population. Local administrations commonly use flow propagation models to delineate the flood prone areas. These modeling approaches require a detail geo-environmental data knowledge, intensive...

["Data Mining and Machine Learning","Spatial and Geographic Information Systems"]
doi:10.7287/peerj.preprints.1937v2
92 downloads
302 views

Forest trees cover just over 30% of the earth's surface and are studied by researchers around the world for both their conservation and economic value. With the onset of high throughput technologies, tremendous phenotypic and genomic data sets have been generated...

["Bioinformatics","Data Mining and Machine Learning","Databases"]
doi:10.7287/peerj.preprints.2345v4
180 downloads
317 views

Software energy consumption is a performance related non-functional requirement that complicates building software on mobile devices today. Energy hogging applications are a liability to both the end-user and software developer. Measuring software energy consumption...

["Data Mining and Machine Learning","Mobile and Ubiquitous Computing","Software Engineering"]
doi:10.7287/peerj.preprints.2419v2
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