Anymatrix: an extensible MATLAB matrix collection

Numerical Algorithms ◽

10.1007/s11075-021-01226-2 ◽

2021 ◽

Author(s):

Nicholas J. Higham ◽

Mantas Mikaitis

Keyword(s):

Public Repository ◽

Matlab Toolbox ◽

Matrix Properties ◽

Boolean Expressions

AbstractAnymatrix is a MATLAB toolbox that provides an extensible collection of matrices with the ability to search the collection by matrix properties. Each matrix is implemented as a MATLAB function and the matrices are arranged in groups. Compared with previous collections, Anymatrix offers three novel features. First, it allows a user to share a collection of matrices by putting them in a group, annotating them with properties, and placing the group on a public repository, for example on GitHub; the group can then be incorporated into another user’s local Anymatrix installation. Second, it provides a tool to search for matrices by their properties, with Boolean expressions supported. Third, it provides organization into sets, which are subsets of matrices from the whole collection appended with notes, which facilitate reproducible experiments. Anymatrix comes with 146 built-in matrices organized into 7 groups with 49 recognized properties. The authors continue to extend the collection and welcome contributions from the community.

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A Practitioner's Guide and MATLAB Toolbox for Mixed Frequency State Space Models

SSRN Electronic Journal ◽

10.2139/ssrn.3532455 ◽

2020 ◽

Author(s):

Scott A. Brave ◽

R. Butters ◽

David Kelley

Keyword(s):

State Space ◽

State Space Models ◽

Matlab Toolbox ◽

Mixed Frequency ◽

Frequency State

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Efficient automated localization of ECoG electrodes in CT images via shape analysis

International Journal of Computer Assisted Radiology and Surgery ◽

10.1007/s11548-021-02325-0 ◽

2021 ◽

Vol 16 (4) ◽

pp. 543-554

Author(s):

Jessica Centracchio ◽

Antonio Sarno ◽

Daniele Esposito ◽

Emilio Andreozzi ◽

Luigi Pavone ◽

...

Keyword(s):

Shape Analysis ◽

Focal Epilepsy ◽

Support Vector ◽

Epileptogenic Zone ◽

Platinum Electrodes ◽

Public Repository ◽

Automated Method ◽

Depth Electrodes ◽

Ethical Approval ◽

Cortical Regions

Abstract Purpose People with drug-refractory epilepsy are potential candidates for surgery. In many cases, epileptogenic zone localization requires intracranial investigations, e.g., via ElectroCorticoGraphy (ECoG), which uses subdural electrodes to map eloquent areas of large cortical regions. Precise electrodes localization on cortical surface is mandatory to delineate the seizure onset zone. Simple thresholding operations performed on patients’ computed tomography (CT) volumes recognize electrodes but also other metal objects (e.g., wires, stitches), which need to be manually removed. A new automated method based on shape analysis is proposed, which provides substantially improved performances in ECoG electrodes recognition. Methods The proposed method was retrospectively tested on 24 CT volumes of subjects with drug-refractory focal epilepsy, presenting a large number (> 1700) of round platinum electrodes. After CT volume thresholding, six geometric features of voxel clusters (volume, symmetry axes lengths, circularity and cylinder similarity) were used to recognize the actual electrodes among all metal objects via a Gaussian support vector machine (G-SVM). The proposed method was further tested on seven CT volumes from a public repository. Simultaneous recognition of depth and ECoG electrodes was also investigated on three additional CT volumes, containing penetrating depth electrodes. Results The G-SVM provided a 99.74% mean classification accuracy across all 24 single-patient datasets, as well as on the combined dataset. High accuracies were obtained also on the CT volumes from public repository (98.27% across all patients, 99.68% on combined dataset). An overall accuracy of 99.34% was achieved for the recognition of depth and ECoG electrodes. Conclusions The proposed method accomplishes automated ECoG electrodes localization with unprecedented accuracy and can be easily implemented into existing software for preoperative analysis process. The preliminary yet surprisingly good results achieved for the simultaneous depth and ECoG electrodes recognition are encouraging. Ethical approval n°NCT04479410 by “IRCCS Neuromed” (Pozzilli, Italy), 30th July 2020.

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A-Tree: A Dynamic Data Structure for Efficiently Indexing Arbitrary Boolean Expressions

Proceedings of the 2021 International Conference on Management of Data ◽

10.1145/3448016.3457266 ◽

2021 ◽

Author(s):

Shuping Ji ◽

Hans-Arno Jacobsen

Keyword(s):

Data Structure ◽

Dynamic Data ◽

Dynamic Data Structure ◽

Boolean Expressions

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Constrained Petri Nets. Part II: Generalizations and extensions

Fundamenta Informaticae ◽

10.3233/fi-1983-63-408 ◽

1983 ◽

Vol 6 (3-4) ◽

pp. 333-374

Author(s):

H.J.M. Goeman ◽

L.P.J. Groenewegen ◽

H.C.M. Kleijn ◽

G. Rozenberg

Keyword(s):

Petri Nets ◽

Petri Net ◽

Theoretical Framework ◽

General Constraints ◽

Context Free ◽

Boolean Expressions

This paper continues the investigation froll1 [Goeman et al.] concerning the use of sets of places of a Petri net as additional (to input places) constraints for granting concession. Now interpretations of more general constraints are considered and expressed as Boolean expressions. This gives rise to various classes of constrained Petri nets. These are compared in the language theoretical framework introduced in [Goeman et al.]. An upperbound for the language defining power is found in the class of context-free programmed languages.

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