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.

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 CFTR Lifecycle Map—A Systems Medicine Model of CFTR Maturation to Predict Possible Active Compound Combinations

2021 ◽  
Vol 22 (14) ◽  
pp. 7590
Author(s):  
Liza Vinhoven ◽  
Frauke Stanke ◽  
Sylvia Hafkemeyer ◽  
Manuel Manfred Nietert
Keyword(s):  
Large Scale ◽  
Synergistic Effects ◽  
Small Scale ◽  
Systems Medicine ◽  
Promising Candidate ◽  
Cftr Mutations ◽  
Machine Readable ◽  
High Throughput Screens ◽  
Readable Format ◽  
Machine Readable Format

Different causative therapeutics for CF patients have been developed. There are still no mutation-specific therapeutics for some patients, especially those with rare CFTR mutations. For this purpose, high-throughput screens have been performed which result in various candidate compounds, with mostly unclear modes of action. In order to elucidate the mechanism of action for promising candidate substances and to be able to predict possible synergistic effects of substance combinations, we used a systems biology approach to create a model of the CFTR maturation pathway in cells in a standardized, human- and machine-readable format. It is composed of a core map, manually curated from small-scale experiments in human cells, and a coarse map including interactors identified in large-scale efforts. The manually curated core map includes 170 different molecular entities and 156 reactions from 221 publications. The coarse map encompasses 1384 unique proteins from four publications. The overlap between the two data sources amounts to 46 proteins. The CFTR Lifecycle Map can be used to support the identification of potential targets inside the cell and elucidate the mode of action for candidate substances. It thereby provides a backbone to structure available data as well as a tool to develop hypotheses regarding novel therapeutics.

scholarly journals Pangeo Forge: Crowdsourcing Analysis-Ready, Cloud Optimized Data Production

2021 ◽  
Author(s):  
Charles Stern ◽  
Ryan Abernathey ◽  
Joseph Hamman ◽  
Rachel Wegener ◽  
Chiara Lepore ◽  
...  
Keyword(s):  
Big Data ◽  
Open Source ◽  
Climate Science ◽  
Cloud Infrastructure ◽  
Scientific Domain ◽  
Weather And Climate ◽  
Data Production ◽  
New Community ◽  
High Level ◽  
Machine Readable

Pangeo Forge is a new community-driven platform that accelerates science by providing high-level recipe frameworks alongside cloud compute infrastructure for extracting data from provider archives, transforming it into analysis-ready, cloud-optimized (ARCO) data stores, and providing a human- and machine-readable catalog for browsing and loading. In abstracting the scientific domain logic of data recipes from cloud infrastructure concerns, Pangeo Forge aims to open a door for a broader community of scientists to participate in ARCO data production. A wholly open-source platform composed of multiple modular components, Pangeo Forge presents a foundation for the practice of reproducible, cloud-native, big-data ocean, weather, and climate science without relying on proprietary or cloud-vendor-specific tooling.

Implementation of Programming Languages Syntax and Semantics

2011 ◽  
pp. 1863-1869
Author(s):  
Xiaoqing Wu ◽  
Marjan Mernik ◽  
Barrett R. Bryant ◽  
Jeff Gray
Keyword(s):  
Programming Languages ◽  
Semantic Analysis ◽  
Implementation Process ◽  
Future Trends ◽  
Human Communication ◽  
Natural Languages ◽  
Existing Problems ◽  
Front End ◽  
High Level ◽  
Machine Readable

Unlike natural languages, programming languages are strictly stylized entities created to facilitate human communication with computers. In order to make programming languages recognizable by computers, one of the key challenges is to describe and implement language syntax and semantics such that the program can be translated into machine-readable code. This process is normally considered as the front-end of a compiler, which is mainly related to the programming language, but not the target machine. This article will address the most important aspects in building a compiler front-end; that is, syntax and semantic analysis, including related theories, technologies and tools, as well as existing problems and future trends. As the main focus, formal syntax and semantic specifications will be discussed in detail. The article provides the reader with a high-level overview of the language implementation process, as well as some commonly used terms and development practices.

A Design Tool for Business Process Design and Representation

2010 ◽  
pp. 160-177
Author(s):  
Roberto Paiano ◽  
Anna Lisa Guido
Keyword(s):  
Business Process ◽  
Process Design ◽  
Design Tool ◽  
Formal Representation ◽  
Middle Point ◽  
Business Process Design ◽  
Semantic Web Technology ◽  
Web Information System ◽  
Machine Readable ◽  
Readable Format

In this chapter the focus is on business process design as middle point between requirement elicitation and implementation of a Web information system. We face both the problem of the notation to adopt in order to represent in a simple way the business process and the problem of a formal representation, in a machine-readable format, of the design. We adopt Semantic Web technology to represent process and we explain how this technology has been used to reach our goals.

A Design Tool for Business Process Design and Representation

2009 ◽  
pp. 451-468
Author(s):  
Roberto Paiano ◽  
Anna Lisa Guido
Keyword(s):  
Business Process ◽  
Process Design ◽  
Design Tool ◽  
Formal Representation ◽  
Middle Point ◽  
Business Process Design ◽  
Semantic Web Technology ◽  
Web Information System ◽  
Machine Readable ◽  
Readable Format

In this chapter the focus is on business process design as middle point between requirement elicitation and implementation of a Web information system. We face both the problem of the notation to adopt in order to represent in a simple way the business process and the problem of a formal representation, in a machine-readable format, of the design. We adopt Semantic Web technology to represent process and we explain how this technology has been used to reach our goals.

Dynamical entropic analysis of scientific concepts

2020 ◽  
pp. 016555152097203
Author(s):  
Artem Chumachenko ◽  
Boris Kreminskyi ◽  
Iurii Mosenkis ◽  
Alexander Yakimenko
Keyword(s):  
Scientific Progress ◽  
Knowledge Mapping ◽  
Scientific Publications ◽  
Actual Structure ◽  
Information Theoretic ◽  
Semantic Component ◽  
Human Interpretation ◽  
Basic Concepts ◽  
Machine Readable ◽  
Readable Format

In the present era of information, the problem of effective knowledge retrieval from a collection of scientific documents becomes especially important for continuous scientific progress. The information available in scientific publications traditionally consists of bibliometric metadata and its semantic component such as title, abstract and text. While the former having a machine-readable format usually used for knowledge mapping and pattern recognition, the latter designed for human interpretation and analysis. Only a few studies use full-text analysis, based on carefully selected scientific ontology, to map the actual structure of the scientific knowledge or uncover similarities between documents. Unfortunately, the presence of common (basic) concepts across semantically unrelated documents creates spurious connections between different topics. We revise the known method based on the entropic information-theoretic measure used for selecting basic concepts and propose to analyse the dynamics of Shannon entropy for more rigorous sorting of concepts by their generality.

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