A Principle of Correlativity of Perception and Its Application to Music Recognition

1994 ◽  
Vol 11 (4) ◽  
pp. 465-502 ◽  
Author(s):  
A. S. Tanguiane
Keyword(s):  
Kolmogorov Complexity ◽  
Data Representation ◽  
Abstract Thinking ◽  
Complex Data ◽  
Data Generation ◽  
Rhythm Perception ◽  
Semantic Description ◽  
Memory Store ◽  
Music Recognition ◽  
High Level

Correlativity of perception is defined as a capacity to discover similar configurations of stimuli and to form high- level configurations from them. It is equivalent to describing information in terms of generative elements and their transformations. Such a representation saves memory and reveals causality in data generation. This approach is implemented in a model of artificial perception wherein data are selforganized in order to segregate patterns before recognizing them. Input information is described as generative patterns and their transformations. The least complex data representation that leads to a causally related semantic description is chosen, with (Kolmogorov) complexity defined by the amount of memory store required. The model is applied to voice separation and to rhythm/tempo tracking. Chord spectra are described by generative subspectra, which correspond to tonal spectra, and by their translations, which coincide with the intervals of the chord. Time events are also described by generative rhythmic patterns. Tempo and rhythm interdependence is overcome by the optimal sharing of complexity between representations of rhythmic patterns and tempo curve. The model explains the function of interval hearing, certain statements of music theory, and some effects of rhythm perception. Applications to image processing and modeling of abstract thinking are also discussed.

scholarly journals Data Reduction in the String Space for Efficient kNN Classification Through Space Partitioning

2020 ◽  
Vol 10 (10) ◽  
pp. 3356 ◽  
Author(s):  
Jose J. Valero-Mas ◽  
Francisco J. Castellanos
Keyword(s):  
Data Reduction ◽  
Structural Data ◽  
Data Representation ◽  
Space Partitioning ◽  
Classification Rate ◽  
Symbolic Data ◽  
Knn Classifier ◽  
Initial Dataset ◽  
Low Efficiency ◽  
High Level

Within the Pattern Recognition field, two representations are generally considered for encoding the data: statistical codifications, which describe elements as feature vectors, and structural representations, which encode elements as high-level symbolic data structures such as strings, trees or graphs. While the vast majority of classifiers are capable of addressing statistical spaces, only some particular methods are suitable for structural representations. The kNN classifier constitutes one of the scarce examples of algorithms capable of tackling both statistical and structural spaces. This method is based on the computation of the dissimilarity between all the samples of the set, which is the main reason for its high versatility, but in turn, for its low efficiency as well. Prototype Generation is one of the possibilities for palliating this issue. These mechanisms generate a reduced version of the initial dataset by performing data transformation and aggregation processes on the initial collection. Nevertheless, these generation processes are quite dependent on the data representation considered, being not generally well defined for structural data. In this work we present the adaptation of the generation-based reduction algorithm Reduction through Homogeneous Clusters to the case of string data. This algorithm performs the reduction by partitioning the space into class-homogeneous clusters for then generating a representative prototype as the median value of each group. Thus, the main issue to tackle is the retrieval of the median element of a set of strings. Our comprehensive experimentation comparatively assesses the performance of this algorithm in both the statistical and the string-based spaces. Results prove the relevance of our approach by showing a competitive compromise between classification rate and data reduction.

scholarly journals Associations Between Music Training and the Dynamics of Writing Music by Hand

2020 ◽  
pp. 102986492097214
Author(s):  
Aurélien Bertiaux ◽  
François Gabrielli ◽  
Mathieu Giraud ◽  
Florence Levé
Keyword(s):  
Classical Music ◽  
Music Notation ◽  
Musical Score ◽  
Music Training ◽  
Video Recordings ◽  
Musical Structures ◽  
Music Recognition ◽  
High Level ◽  
Bottom To Top ◽  
Western Classical Music

Learning to write music in the staff notation used in Western classical music is part of a musician’s training. However, writing music by hand is rarely taught formally, and many musicians are not aware of the characteristics of their musical handwriting. As with any symbolic expression, musical handwriting is related to the underlying cognition of the musical structures being depicted. Trained musicians read, think, and play music with high-level structures in mind. It seems natural that they would also write music by hand with these structures in mind. Moreover, improving our understanding of handwriting may help to improve both optical music recognition and music notation and composition interfaces. We investigated associations between music training and experience, and the way people write music by hand. We made video recordings of participants’ hands while they were copying or freely writing music, and analysed the sequence in which they wrote the elements contained in the musical score. The results confirmed experienced musicians wrote faster than beginners, were more likely to write chords from bottom to top, and they tended to write the note heads first, in a flowing fashion, and only afterwards use stems and beams to emphasize grouping, and add expressive markings.

A Form Verification System for the Conceptual Design of Complex Mechanical Systems

1993 ◽  
Author(s):  
Jonathan S. Colton ◽  
Mark P. Ouellette
Keyword(s):  
Conceptual Design ◽  
Process Model ◽  
Mechanical Systems ◽  
Data Representation ◽  
Design System ◽  
Complex Data ◽  
Graphical Display ◽  
Design Environment ◽  
Blackboard System ◽  
Complex Mechanical Systems

Abstract This paper presents a summary of research into the development and implementation of a domain independent, computer-based model for the conceptual design of complex mechanical systems (Ouellette, 1992). The creation of such a design model includes the integration of four major concepts: (1) The use of a graphical display for visualizing the conceptual design attributes; (2) The proper representation of the complex data and diverse knowledge required to design the system; (3) The integration of quality design methods into the conceptual design; and (4) The modeling of the conceptual design process as a mapping between functions and forms. Using the design of an automobile as a case study, a design environment was created which consisted of a distributed problem solving paradigm and a parametric graphical display. The requirements of the design problem with respect to data representation and design processing were evaluated and a process model was specified. The resulting vehicle design system consists of a tight integration between a blackboard system and a parametric design system. The completed system allows a designer to view graphical representations of the candidate conceptual designs that the blackboard system generates.

scholarly journals Tree-Shaped Formats of Address Programming Language

2021 ◽  
Vol 4 ◽  
pp. 78-87
Author(s):  
Yury Yuschenko
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Theoretical Research ◽  
Direct Access ◽  
Complex Data ◽  
Abstract Data Types ◽  
Data Types ◽  
Abstract Data ◽  
The One ◽  
High Level

In the Address Programming Language (1955), the concept of indirect addressing of higher ranks (Pointers) was introduced, which allows the arbitrary connection of the computer’s RAM cells. This connection is based on standard sequences of the cell addresses in RAM and addressing sequences, which is determined by the programmer with indirect addressing. Two types of sequences allow programmers to determine an arbitrary connection of RAM cells with the arbitrary content: data, addresses, subroutines, program labels, etc. Therefore, the formed connections of cells can relate to each other. The result of connecting cells with the arbitrary content and any structure is called tree-shaped formats. Tree-shaped formats allow programmers to combine data into complex data structures that are like abstract data types. For tree-shaped formats, the concept of “review scheme” is defined, which is like the concept of “bypassing” trees. Programmers can define multiple overview diagrams for the one tree-shaped format. Programmers can create tree-shaped formats over the connected cells to define the desired overview schemes for these connected cells. The work gives a modern interpretation of the concept of tree-shaped formats in Address Programming. Tree-shaped formats are based on “stroke-operation” (pointer dereference), which was hardware implemented in the command system of computer “Kyiv”. Group operations of modernization of computer “Kyiv” addresses accelerate the processing of tree-shaped formats and are designed as organized cycles, like those in high-level imperative programming languages. The commands of computer “Kyiv”, due to operations with indirect addressing, have more capabilities than the first high-level programming language – Plankalkül. Machine commands of the computer “Kyiv” allow direct access to the i-th element of the “list” by its serial number in the same way as such access is obtained to the i-th element of the array by its index. Given examples of singly linked lists show the features of tree-shaped formats and their differences from abstract data types. The article opens a new branch of theoretical research, the purpose of which is to analyze the expe- diency of partial inclusion of Address Programming in modern programming languages.

Authentication of Educational Practices in Online Learning

2021 ◽  
pp. 52-66
Author(s):  
O.V. Lukyanov ◽  
◽  
I.A. Dubinina ◽  
E.V. Bredun ◽  
◽  
...  
Keyword(s):  
Online Learning ◽  
Online Education ◽  
Learning Environment ◽  
Individual Learning ◽  
Educational Process ◽  
Educational Practices ◽  
Abstract Thinking ◽  
Field Independence ◽  
High Coefficient ◽  
High Level

The aim of online learning is to help forward the individualization of educational practices and self-determination of a student. From the technological point of view, it is supposed to reduce the costs on the teacher’s presence in educational process (it is not a teacher but a plat-form which holds the knowledge) and to increase investments in the student’s presence (a student completes the given knowledge with his own senses, motives, values and creativity). An important phase of educational process is rating. According to the trend of “high technolo-gies” (technologies that minimize the human presence in management) we may say that there is also a trend to increase the level of rating. In online learning environment we rate not only the results and actions of a student, but also the level of his abilities or competence and the means of rating authenticity. The article discusses the data received on using the “Self-attestation practice” online course. It is a means of final assessment for students who complete the BA in psychology. By the way of variance analysis, we verified the hypothesis that the high level of abstract thinking, high coefficient of categorization, high level of creativity, field independence and reflexivity on cognitive styles are favor for intellectual productivity in scientific, research and creative areas. A measured set of level characteristics for intellectual products is transformed into a com-plex of observed language qualities. The high level of abstract thinking is demonstrated in speech coherence, in discourse consistency. The high coefficient of categorization is demon-strated in the ability to interpret texts into different languages and scales. High creativity level can be seen in making preference for difficult, challenging creative tasks. Field independence and reflexivity is demonstrated in the ability to make an individual educational track. These characteristics are markers of successful study, including online education. They allow us esti-mating each student’s involvement into professional studies and defining the levels of intellectual success, predicting the model of individual learning environment (individual learning track).

Parametric Generator for Architectural and Urban 3D Objects

2013 ◽  
pp. 260-267
Author(s):  
Renato Saleri Lunazzi
Keyword(s):  
Finite Elements ◽  
Conceptual Model ◽  
Geometric Modeling ◽  
General Purpose ◽  
Semantic Description ◽  
3D Objects ◽  
Future Developments ◽  
Simple Tool ◽  
Parametric Generator ◽  
High Level

The authors developed and finalized a specific tool able to model the global structure of architectural objects through a morphological and semantic description of its finite elements. This discrete conceptual model - still in study - was refined during the geometric modeling of the “Vieux Lyon” district, containing a high level of morpho-stylistic disparity. Future developments should allow increasing the genericity of its descriptive efficiency, permitting even more sparse morphological and\or stylistic varieties. Its general purpose doesn’t consist in creating a “universal modeler,” but to offer a simple tool able to quickly describe a majority of standard architectural objects compliant with some standard parametric definition rules.

Optical Music Analysis for Printed Music Score and Handwritten Music Manuscript

2011 ◽  
pp. 108-127 ◽  
Author(s):  
Kia Ng
Keyword(s):  
Domain Knowledge ◽  
Imaging System ◽  
Data Representation ◽  
Divide And Conquer ◽  
Music Score ◽  
Segmentation Approach ◽  
Printed Music ◽  
High Level ◽  
Machine Readable ◽  
Readable Format

This chapter describes an optical document imaging system to transform paper-based music scores and manuscripts into machine-readable format and a restoration system to touch-up small imperfections (for example broken stave lines and stems), to restore deteriorated master copy for reprinting. The chapter presents a brief background of this field, discusses the main obstacles, and presents the processes involved for printed music scores processing; using a divide-and-conquer approach to sub-segment compound musical symbols (e.g., chords) and inter-connected groups (e.g., beamed quavers) into lower-level graphical primitives (e.g., lines and ellipses) before recognition and reconstruction. This is followed by discussions on the developments of a handwritten manuscripts prototype with a segmentation approach to separate handwritten musical primitives. Issues and approaches for recognition, reconstruction and revalidation using basic music syntax and high-level domain knowledge, and data representation are also presented.

Information Model Governance for Diverse Disciplines

2020 ◽  
Author(s):  
John S. Hughes ◽  
Daniel J. Crichton
Keyword(s):  
Reference Model ◽  
Configuration Management ◽  
Information Model ◽  
Data Representation ◽  
Planetary Science ◽  
Complex Data ◽  
Data Types ◽  
The Common ◽  
Multi Level ◽  
Science Disciplines

<p>The PDS4 Information Model (IM) Version 1.13.0.0 was released for use in December 2019. The ontology-based IM remains true to its foundational principles found in the Open Archive Information System (OAIS) Reference Model (ISO 14721) and the Metadata Registry (MDR) standard (ISO/IEC 11179). The standards generated from the IM have become the de-facto data archiving standards for the international planetary science community and have successfully scaled to meet the requirements of the diverse and evolving planetary science disciplines.</p><p>A key foundational principle is the use of a multi-level governance scheme that partitions the IM into semi-independent dictionaries. The governance scheme first partitions the IM vertically into three levels, the common, discipline, and project/mission levels. The IM is then partitioned horizontally across both discipline and project/mission levels into individual Local Data Dictionaries (LDDs).</p><p>The Common dictionary defines the classes used across the science disciplines such as product, collection, bundle, data formats, data types, and units of measurement. The dictionary resulted from a large collaborative effort involving domain experts across the community. An ontology modeling tool was used to enforce a modeling discipline, for configuration management, to ensure consistency and extensibility, and to enable interoperability. The Common dictionary encompasses the information categories defined in the OAIS RM, specifically data representation, provenance, fixity, identification, reference, and context. Over the last few years, the Common dictionary has remained relatively stable in spite of requirements levied by new missions, instruments, and more complex data types.</p><p>Since the release of the Common dictionary, the creation of a significant number of LDDs has proved the effectiveness of multi-level, steward-based governance. This scheme is allowing the IM to scale to meet the archival and interoperability demands of the evolving disciplines. In fact, an LDD development “cottage industry” has emerged that required improvements to the development processes and configuration management.  An LDD development tool now allows dictionary stewards to quickly produce specialized LDDs that are consistent with the Common dictionary.</p><p>The PDS4 Information Model is a world-class knowledge-base that governs the Planetary Science community's trusted digital repositories. This presentation will provide an overview of the model and additional information about its multi-level governance scheme including the topics of stewardship, configuration management, processes, and oversight.</p>

scholarly journals The PlaNet Consortium: A Network of European Plant Databases Connecting Plant Genome Data in an Integrated Biological Knowledge Resource

2004 ◽  
Vol 5 (2) ◽  
pp. 184-189 ◽  
Author(s):  
H. Schoof ◽  
R. Ernst ◽  
K. F. X. Mayer
Keyword(s):  
Data Exchange ◽  
Data Representation ◽  
Data Models ◽  
Biological Data ◽  
Plant Genome ◽  
Data Sources ◽  
Direct Access ◽  
Biological Knowledge ◽  
Database Integration ◽  
Complex Data

The completion of theArabidopsisgenome and the large collections of other plant sequences generated in recent years have sparked extensive functional genomics efforts. However, the utilization of this data is inefficient, as data sources are distributed and heterogeneous and efforts at data integration are lagging behind. PlaNet aims to overcome the limitations of individual efforts as well as the limitations of heterogeneous, independent data collections. PlaNet is a distributed effort among European bioinformatics groups and plant molecular biologists to establish a comprehensive integrated database in a collaborative network. Objectives are the implementation of infrastructure and data sources to capture plant genomic information into a comprehensive, integrated platform. This will facilitate the systematic exploration ofArabidopsisand other plants. New methods for data exchange, database integration and access are being developed to create a highly integrated, federated data resource for research. The connection between the individual resources is realized with BioMOBY. BioMOBY provides an architecture for the discovery and distribution of biological data through web services. While knowledge is centralized, data is maintained at its primary source without a need for warehousing. To standardize nomenclature and data representation, ontologies and generic data models are defined in interaction with the relevant communities.Minimal data models should make it simple to allow broad integration, while inheritance allows detail and depth to be added to more complex data objects without losing integration. To allow expert annotation and keep databases curated, local and remote annotation interfaces are provided. Easy and direct access to all data is key to the project.

scholarly journals Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

2003 ◽  
Vol 15 (6) ◽  
pp. 1373-1396 ◽  
Author(s):  
Mikhail Belkin ◽  
Partha Niyogi
Keyword(s):  
Dimensionality Reduction ◽  
Dimensional Space ◽  
Graph Laplacian ◽  
Data Representation ◽  
Beltrami Operator ◽  
High Dimensional ◽  
Nonlinear Dimensionality Reduction ◽  
Complex Data ◽  
Dimensional Manifold ◽  
Natural Connection

One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complex data. We consider the problem of constructing a representation for data lying on a low-dimensional manifold embedded in a high-dimensional space. Drawing on the correspondence between the graph Laplacian, the Laplace Beltrami operator on the manifold, and the connections to the heat equation, we propose a geometrically motivated algorithm for representing the high-dimensional data. The algorithm provides a computationally efficient approach to nonlinear dimensionality reduction that has locality-preserving properties and a natural connection to clustering. Some potential applications and illustrative examples are discussed.

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