Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from http://scikit-learn.sourceforge.net.

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Scikit-learn: Machine Learning in Python

LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popularity in machine learning and many other areas. In this article, we present all implementation details of LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.

/pdf/libsvm-a-library-for-support-vector-machines-2gdxasg9zv.pdf

LIBSVM: A library for support vector machines

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from this http URL.

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

J. Appl. Cryst.の発刊に際して

In the present paper we report on structural investigations of fivefold In0.2Ga0.8As/GaAs superlattices which have been grown by means of metal organic chemical vapor deposition on vicinal GaAs(001) substrates. Cross-sectional transmission electron micrographs exhibit an initially flat and nonfaceted grooved surface, while step bunching occurs during subsequent growth stages with an inclined vertical inheritance approximately 45° off the (001) direction. A reconstructed sample cross section on the base of high resolution x-ray diffraction data qualitatively confirms the local morphology proved by transmission electron microscopy. Moreover, a line shape analysis of diffusely scattered intensity using Gauss profiles indicates a lateral short range ordering of step bunches.

/pdf/lateral-short-range-ordering-of-step-bunches-in-ingaas-gaas-21r9nui8sv.pdf

Lateral short range ordering of step bunches in InGaAs/GaAs superlattices

/pdf/nfdi-neuro-building-a-community-for-neuroscience-research-sqgjxnzusz.pdf

NFDI-Neuro: building a community for neuroscience research data management in Germany

The impact of the GaAs spacer layer thickness on the three-dimensional ordering in In, GaAs/ GaAs311B quantum dot superlattices was investigated by high-resolution x-ray diffraction, cross-sectional transmission electron microscopy, and atomic force microscopy. Dramatic changes in both planar and vertical ordering could be observed. A distinct correlation was found in that the azimuthal angle of inclined vertical inheritance of the dot positions is perpendicular to the planar direction between the dot chains within individual quantum dot layers. These directions are close to 130 or 1 03 .© 2009 American Institute of Physics. DOI: 10.1063/1.3141404

/pdf/peculiar-three-dimensional-ordering-in-in-ga-as-gaas-311-b-ku9xb5l5o7.pdf

Peculiar three-dimensional ordering in (In,Ga)As/GaAs(311)B quantum dot superlattices

InP(111) surfaces are sulfurized using vaporized Sb2S3 and Bi2S3 as the providers of S. Temperatures higher than 340 °C are required to substitute the Sb atoms in Sb2S3 with the In atoms from the s...

Surfactant-Induced Alterations of Epitaxial Orientation in β-In2S3 Layers on InP

Here we extend the information on the structure of the core stimulus of the studyforrest project (http://studyforrest.org) with a description of semantic conflict in the “Forrest Gump” movie. Three observers annotated the movie independently regarding episodes with portrayal of lies, irony or sarcasm. We present frequency statistics, and inter-observer reliability measures that qualify and quantify semantic conflict in the stimulus. While the number of identified events is limited, this annotation nevertheless enriches the knowledge about the complex high-level structure of this stimulus, and can help to evaluate its utility for future studies, and the usability of the existing brain imaging data regarding this aspect of cognition.

Michael Hanke

Papers

Lateral short range ordering of step bunches in InGaAs/GaAs superlattices

NFDI-Neuro: building a community for neuroscience research data management in Germany

Peculiar three-dimensional ordering in (In,Ga)As/GaAs(311)B quantum dot superlattices

Surfactant-Induced Alterations of Epitaxial Orientation in β-In2S3 Layers on InP

Lies, irony, and contradiction - an annotation of semantic conflict in the movie "Forrest Gump".