scholarly journals A VTK Algorithm for the Computation of the Hausdorff Distance

2011 ◽  
Author(s):  
Frédéric Commandeur ◽  
Jérôme Velut ◽  
Oscar Acosta
Keyword(s):  
Hausdorff Distance ◽  
Similarity Measures ◽  
Point To Point ◽  
Definition Of

The Hausdorff distance is a measure of the distance between sets of points. There are many advantages to using this metric compared to other similarity measures. This document describes a VTK class for computing the Hausdorff Distance between two sets of points. The main contribution, compared to other implementations, lies in the definition of the distance not only to the closest point but to the closest point in the represented surface, which yields an accurate measure even between undersampled surfaces. This is achieved by implementing a point-to-cell distance instead of a point-to-point. Furthermore, a plugin for ParaView was implemented, which is also available with the code. After introducing the interest of this distance, the VTK code is explained and illustrated with some examples.

Issues of organizing computations in multicomputersystems with the software-controlled failure- and fault-tolerance. Part 1

2021 ◽  
Author(s):  
I.V. Asharina
Keyword(s):  
Fault Tolerance ◽  
Critical Level ◽  
Fault Tolerant ◽  
Communication Channels ◽  
State Standards ◽  
Modern Concept ◽  
Multiple Faults ◽  
Point To Point ◽  
Definition Of ◽  
Test Diagnostics

This three-part paper analyzes existing approaches and methods of organizing failure- and fault-tolerant computing in distributed multicomputer systems (DMCS), identifies and provides rationale for a list of issues to be solved. We present the concept of fault tolerance proposed by A. Avizienis, explicate its dissimilarity from the modern concept and the reason for its inapplicability with regard to modern distributed multicomputer systems. We justify the necessity to refine the definition of fault tolerance approved by the State Standards, as well as the necessity to specify three input parameters to be taken into account in the DMCS design methods: permitted fault models, permitted multiplicity of faults, permitted fault sequence capabilities. We formulate the questions that must be answered in order to design a truly reliable, fault-tolerant system and consider the application areas of the failure- and fault-tolerant control systems for complex network and distributed objects. System, functional, and test diagnostics serve as the basis for building unattended failure- and fault-tolerant systems. The concept of self-managed degradation (with the DMCS eventually proceeding to a safe shutdown at a critical level of degradation) is a means to increase the DMCS active life. We consider the issues related to the diagnosis of multiple faults and present the main differences in ensuring fault tolerance between systems with broadcast communication channels and systems with point-to-point communication channels. The first part of the work mainly deals with the analysis of existing approaches and methods of organizing failure- and fault-tolerant computing in DMCS and the definition of the concept of fault-tolerance.

New Similarity Measures between Vague Sets and Performance Analysis

2013 ◽  
Vol 811 ◽  
pp. 547-551 ◽  
Author(s):  
Hong Xu Wang ◽  
Hai Feng Wang ◽  
Kun Zhang ◽  
Hui Wang
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Similarity Measure ◽  
Similarity Measures ◽  
Practical Case ◽  
Vague Sets ◽  
Diagnosis Method ◽  
And Performance ◽  
Definition Of ◽  
New Formula

In order to amend the defects of existing similarity measure formula between vague sets, a new definition of similarity measure between vague sets is proposed and a new formula with higher resolution and highlighted uncertainty is presented on the basis of data mining vague value method. A general fault diagnosis method of Vague sets (GFDMVS) is proposed. The same practical case is studied with three methods and the results demonstrate the validity and reasonability of the method proposed in this paper.

scholarly journals Co-occurrence Retrieval: A Flexible Framework for Lexical Distributional Similarity

2005 ◽  
Vol 31 (4) ◽  
pp. 439-475 ◽  
Author(s):  
Julie Weeds ◽  
David Weir
Keyword(s):  
Language Processing ◽  
Similarity Measures ◽  
Document Retrieval ◽  
Wide Range ◽  
Distributional Similarity ◽  
Potential Applications ◽  
The Difference ◽  
Occurrence Type ◽  
Definition Of ◽  
Relationship Of

Techniques that exploit knowledge of distributional similarity between words have been proposed in many areas of Natural Language Processing. For example, in language modeling, the sparse data problem can be alleviated by estimating the probabilities of unseen co-occurrences of events from the probabilities of seen co-occurrences of similar events. In other applications, distributional similarity is taken to be an approximation to semantic similarity. However, due to the wide range of potential applications and the lack of a strict definition of the concept of distributional similarity, many methods of calculating distributional similarity have been proposed or adopted. In this work, a flexible, parameterized framework for calculating distributional similarity is proposed. Within this framework, the problem of finding distributionally similar words is cast as one of co-occurrence retrieval (CR) for which precision and recall can be measured by analogy with the way they are measured in document retrieval. As will be shown, a number of popular existing measures of distributional similarity are simulated with parameter settings within the CR framework. In this article, the CR framework is then used to systematically investigate three fundamental questions concerning distributional similarity. First, is the relationship of lexical similarity necessarily symmetric, or are there advantages to be gained from considering it as an asymmetric relationship? Second, are some co-occurrences inherently more salient than others in the calculation of distributional similarity? Third, is it necessary to consider the difference in the extent to which each word occurs in each co-occurrence type? Two application-based tasks are used for evaluation: automatic thesaurus generation and pseudo-disambiguation. It is possible to achieve significantly better results on both these tasks by varying the parameters within the CR framework rather than using other existing distributional similarity measures; it will also be shown that any single unparameterized measure is unlikely to be able to do better on both tasks. This is due to an inherent asymmetry in lexical substitutability and therefore also in lexical distributional similarity.

scholarly journals Using Local Alignments for Relation Recognition

2010 ◽  
Vol 38 ◽  
pp. 1-48 ◽  
Author(s):  
S. Katrenko ◽  
P. W. Adriaans ◽  
M. Van Someren
Keyword(s):  
Sequence Similarity ◽  
General Relation ◽  
Similarity Measures ◽  
Semantic Relatedness ◽  
Structural Similarity ◽  
Learning Task ◽  
Semantic Knowledge ◽  
Local Alignment ◽  
Data Sets ◽  
Definition Of

This paper discusses the problem of marrying structural similarity with semantic relatedness for Information Extraction from text. Aiming at accurate recognition of relations, we introduce local alignment kernels and explore various possibilities of using them for this task. We give a definition of a local alignment (LA) kernel based on the Smith-Waterman score as a sequence similarity measure and proceed with a range of possibilities for computing similarity between elements of sequences. We show how distributional similarity measures obtained from unlabeled data can be incorporated into the learning task as semantic knowledge. Our experiments suggest that the LA kernel yields promising results on various biomedical corpora outperforming two baselines by a large margin. Additional series of experiments have been conducted on the data sets of seven general relation types, where the performance of the LA kernel is comparable to the current state-of-the-art results.

scholarly journals Free congruence: an exploration of expanded similarity measures for time series data

2021 ◽  
Author(s):  
Lucas Cassiel Jacaruso
Keyword(s):  
Time Series ◽  
Dynamic Time Warping ◽  
Time Series Data ◽  
Similarity Measures ◽  
Distance Measures ◽  
Series Data ◽  
Time Warping ◽  
Point To Point ◽  
Dynamic Time ◽  
Point Distance

Abstract Time series similarity measures are highly relevant in a wide range of emerging applications including training machine learning models, classification, and predictive modeling. Standard similarity measures for time series most often involve point-to-point distance measures including Euclidean distance and Dynamic Time Warping. Such similarity measures fundamentally require the fluctuation of values in the time series being compared to follow a corresponding order or cadence for similarity to be established. Other existing approaches use local statistical tests to detect structural changes in time series. This paper is spurred by the exploration of a broader definition of similarity, namely one that takes into account the sheer numerical resemblance between sets of statistical properties for time series segments irrespectively of value labeling. Further, the presence of common pattern components between time series segments was examined even if they occur in a permuted order, which would not necessarily satisfy the criteria of more conventional point-to-point distance measures. The newly defined similarity measures were tested on time series data representing over 20 years of cooperation intent expressed in global media sentiment. Tests determined whether the newly defined similarity measures would accurately identify stronger resemblance, on average, for pairings of similar time series segments (exhibiting overall decline) than pairings of differing segments (exhibiting overall decline and overall rise). The ability to identify patterns other than the obvious overall rise or decline that can accurately relate samples is regarded as a first step towards assessing the value of the newly explored similarity measures for classification or prediction. Results were compared with those of Dynamic Time Warping on the same data for context. Surprisingly, the test for numerical resemblance between sets of statistical properties established stronger resemblance for pairings of decline years with greater statistical significance than Dynamic Time Warping on the particular data and sample size used.

scholarly journals Mapping dominant runoff processes: an evaluation of different approaches using similarity measures and synthetic runoff simulations

2016 ◽  
Vol 20 (7) ◽  
pp. 2929-2945 ◽  
Author(s):  
Manuel Antonetti ◽  
Rahel Buss ◽  
Simon Scherrer ◽  
Michael Margreth ◽  
Massimiliano Zappa
Keyword(s):  
Model Building ◽  
Expert Knowledge ◽  
Similarity Measures ◽  
Landscape Classification ◽  
Ungauged Catchments ◽  
Application Range ◽  
Model And Simulation ◽  
Swiss Plateau ◽  
Soil Information ◽  
Definition Of

Abstract. The identification of landscapes with similar hydrological behaviour is useful for runoff and flood predictions in small ungauged catchments. An established method for landscape classification is based on the concept of dominant runoff process (DRP). The various DRP-mapping approaches differ with respect to the time and data required for mapping. Manual approaches based on expert knowledge are reliable but time-consuming, whereas automatic GIS-based approaches are easier to implement but rely on simplifications which restrict their application range. To what extent these simplifications are applicable in other catchments is unclear. More information is also needed on how the different complexities of automatic DRP-mapping approaches affect hydrological simulations. In this paper, three automatic approaches were used to map two catchments on the Swiss Plateau. The resulting maps were compared to reference maps obtained with manual mapping. Measures of agreement and association, a class comparison, and a deviation map were derived. The automatically derived DRP maps were used in synthetic runoff simulations with an adapted version of the PREVAH hydrological model, and simulation results compared with those from simulations using the reference maps. The DRP maps derived with the automatic approach with highest complexity and data requirement were the most similar to the reference maps, while those derived with simplified approaches without original soil information differed significantly in terms of both extent and distribution of the DRPs. The runoff simulations derived from the simpler DRP maps were more uncertain due to inaccuracies in the input data and their coarse resolution, but problems were also linked with the use of topography as a proxy for the storage capacity of soils. The perception of the intensity of the DRP classes also seems to vary among the different authors, and a standardised definition of DRPs is still lacking. Furthermore, we argue not to use expert knowledge for only model building and constraining, but also in the phase of landscape classification.

Hausdorff Distance for Face Recognition

2015 ◽  
pp. 39-46
Keyword(s):  
Face Recognition ◽  
Hausdorff Distance ◽  
Similarity Measures ◽  
Face Verification ◽  
3D Data ◽  
Modified Hausdorff Distance

When two sets are differently sized, the Hausdorff distance can be computed between them, even if the cardinality of one set is infinite. Different versions of this distance have been proposed and employed for face verification, among which the modified Hausdorff distance is the most famous. The important point to be noted is that, among the most commonly used similarity measures, the Hausdorff distance is the only one that has been widely applied to 3D data.

scholarly journals Measures of Probabilistic Neutrosophic Hesitant Fuzzy Sets and the Application in Reducing Unnecessary Evaluation Processes

Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 649 ◽  
Author(s):  
Songtao Shao ◽  
Xiaohong Zhang
Keyword(s):  
Fuzzy Set ◽  
Information Needs ◽  
Distance Measure ◽  
Similarity Measures ◽  
Hesitant Fuzzy Set ◽  
Fuzzy Information ◽  
Entropy Measures ◽  
Subjective Factor ◽  
Measure Model ◽  
Definition Of

Distance measure and similarity measure have been applied to various multi-criteria decision-making environments, like talent selections, fault diagnoses and so on. Some improved distance and similarity measures have been proposed by some researchers. However, hesitancy is reflected in all aspects of life, thus the hesitant information needs to be considered in measures. Then, it can effectively avoid the loss of fuzzy information. However, regarding fuzzy information, it only reflects the subjective factor. Obviously, this is a shortcoming that will result in an inaccurate decision conclusion. Thus, based on the definition of a probabilistic neutrosophic hesitant fuzzy set (PNHFS), as an extended theory of fuzzy set, the basic definition of distance, similarity and entropy measures of PNHFS are established. Next, the interconnection among the distance, similarity and entropy measures are studied. Simultaneously, a novel measure model is established based on the PNHFSs. In addition, the new measure model is compared by some existed measures. Finally, we display their applicability concerning the investment problems, which can be utilized to avoid redundant evaluation processes.

Design of an MRI-Compatible Robotic Stereotactic Device for Minimally Invasive Interventions in the Breast†

2004 ◽  
Vol 126 (4) ◽  
pp. 458-465 ◽  
Author(s):  
Blake T. Larson ◽  
Arthur G. Erdman ◽  
Nikolaos V. Tsekos ◽  
Essa Yacoub ◽  
Panagiotis V. Tsekos ◽  
...  
Keyword(s):  
Real Time ◽  
Degrees Of Freedom ◽  
Rotation Axis ◽  
Interventional Procedure ◽  
Therapeutic Interventions ◽  
Mri Guidance ◽  
Mr Guidance ◽  
Magnetic Resonance Imaging Mri ◽  
Point To Point ◽  
Definition Of

The objective of this work was to develop a robotic device to perform biopsy and therapeutic interventions in the breast with real-time magnetic resonance imaging (MRI) guidance. The device was designed to allow for (i) stabilization of the breast by compression, (ii) definition of the interventional probe trajectory by setting the height and pitch of a probe insertion apparatus, and (iii) positioning of an interventional probe by setting the depth of insertion. The apparatus is fitted with five computer-controlled degrees of freedom for delivering an interventional procedure. The entire device is constructed of MR compatible materials, i.e. nonmagnetic and non-conductive, to eliminate artifacts and distortion of the MR images. The apparatus is remotely controlled by means of ultrasonic motors and a graphical user interface, providing real-time MR-guided planning and monitoring of the operation. Joint motion measurements found probe placement in less than 50 s and sub-millimeter repeatability of the probe tip for same-direction point-to-point movements. However, backlash in the rotation joint may incur probe tip positional errors of up to 5 mm at a distance of 40 mm from the rotation axis, which may occur for women with large breasts. The imprecision caused by this backlash becomes negligible as the probe tip nears the rotation axis. Real-time MR-guidance will allow the physician to correct this error. Compatibility of the device within the MR environment was successfully tested on a 4 Tesla MR human scanner.

Sign in / Sign up

Export Citation Format

Share Document