High Level Programming of Document Classification Systems for Heterogeneous Environments using OpenCL (Abstract Only)

2015 ◽  
Author(s):  
Nasibeh Nasiri ◽  
Oren Segal ◽  
Martin Margala ◽  
Wim Vanderbauwhede ◽  
Sai Rahul Chalamalasetti
Keyword(s):  
Document Classification ◽  
Classification Systems ◽  
Heterogeneous Environments ◽  
High Level

Advanced Applications on Bilingual Document Analysis and Processing Systems

2020 ◽  
Vol 11 (4) ◽  
pp. 149-193
Author(s):  
Shalini Puri ◽  
Satya Prakash Singh
Keyword(s):  
Feature Extraction ◽  
Real Life ◽  
Document Analysis ◽  
Document Classification ◽  
Classification Systems ◽  
Post Processing ◽  
Extraction Techniques ◽  
Dual Class ◽  
Advanced Applications ◽  
Real World Problems

Today, rapid digitization requires efficient bilingual non-image and image document classification systems. Although many bilingual NLP and image-based systems provide solutions for real-world problems, they primarily focus on text extraction, identification, and recognition tasks with limited document types. This article discusses a journey of these systems and provides an overview of their methods, feature extraction techniques, document sets, classifiers, and accuracy for English-Hindi and other language pairs. The gaps found lead toward the idea of a generic and integrated bilingual English-Hindi document classification system, which classifies heterogeneous documents using a dual class feeder and two character corpora. Its non-image and image modules include pre- and post-processing stages and pre-and post-segmentation stages to classify documents into predefined classes. This article discusses many real-life applications on societal and commercial issues. The analytical results show important findings of existing and proposed systems.

Automatic Subject Indexing of Text

2019 ◽  
Vol 46 (2) ◽  
pp. 104-121 ◽  
Author(s):  
Koraljka Golub
Keyword(s):  
Text Categorization ◽  
Document Clustering ◽  
Document Classification ◽  
Classification Systems ◽  
Learning Approach ◽  
Advantages And Disadvantages ◽  
Knowledge Organization Systems ◽  
Machine Learning Approach ◽  
Index Terms ◽  
Subject Indexing

Automatic subject indexing addresses problems of scale and sustainability and can be at the same time used to enrich existing metadata records, establish more connections across and between resources from various metadata and resource collections, and enhance consistency of the metadata. In this work, automatic subject indexing focuses on assigning index terms or classes from established knowledge organization systems (KOSs) for subject indexing like thesauri, subject headings systems and classification systems. The following major approaches are discussed, in terms of their similarities and differences, advantages and disadvantages for automatic assigned indexing from KOSs: “text categorization,” “document clustering,” and “document classification.” Text categorization is perhaps the most widespread, machine-learning approach with what seems generally good reported performance. Document clustering automatically both creates groups of related documents and extracts names of subjects depicting the group at hand. Document classification re-uses the intellectual effort invested into creating a KOS for subject indexing and even simple string-matching algorithms have been reported to achieve good results, because one concept can be described using a number of different terms, including equivalent, related, narrower and broader terms. Finally, applicability of automatic subject indexing to operative information systems and challenges of evaluation are outlined, suggesting the need for more research.

Recent Developments in Information Management for Primary and Community Health Services

1996 ◽  
Vol 26 (4) ◽  
pp. 193-197 ◽  
Author(s):  
Helena Britt ◽  
Graeme Miller
Keyword(s):  
Health Services ◽  
Community Health ◽  
Information Management ◽  
Information Management System ◽  
Community Health Services ◽  
Classification Systems ◽  
Hospital Environment ◽  
Common Data Model ◽  
Recent Developments ◽  
High Level

While health services provided outside the hospital environment are utilised by the majority of the community, until recently there has been little interest in developing a standard approach to information management in community health settings. With greater accountability for health services expected in the future, State and Federal governments have begun to set the necessary standards by the design of a common data model and data definitions for Primary and Community Health Services. This model will affect the manner in which the National Health Data Dictionary develops — from a primarily institution-based document to a broader approach which encompasses non-institutional care. Two new high level concepts have been introduced: “issue” and “activity”. Four States have also formed a consortium to design and implement an information management system for Community Health Services. This necessitates adoption of standard classification systems which could be applied in this environment, especially to the two new high level concepts. This paper outlines recent developments in information management for Community Health and provides a brief summary of available classification systems.

scholarly journals Who is ‘on-call’ in Australia? A new classification approach for on-call employment in future population-level studies

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259035
Author(s):  
Madeline Sprajcer ◽  
Sarah L. Appleton ◽  
Robert J. Adams ◽  
Tiffany K. Gill ◽  
Sally A. Ferguson ◽  
...  
Keyword(s):  
Emergency Services ◽  
Population Level ◽  
Work Conditions ◽  
Classification Systems ◽  
Work Hours ◽  
Work Arrangements ◽  
Standard Work ◽  
High Prevalence ◽  
High Level ◽  
Weekly Work

Background On-call research and guidance materials typically focus on ‘traditional’ on-call work (e.g., emergency services, healthcare). However, given the increasing prevalence of non-standard employment arrangements (e.g., gig work and casualisation), it is likely that a proportion of individuals who describe themselves as being on-call are not included in current on-call literature. This study therefore aimed to describe the current sociodemographic and work characteristics of Australian on-call workers. Methods A survey of 2044 adults assessed sociodemographic and work arrangements. Of this population, 1057 individuals were workforce participants, who were asked to provide information regarding any on-call work they performed over the last three months, occupation type, weekly work hours, and the presence or absence of non-standard work conditions. Results Of respondents who were working, 45.5% reported working at least one day on-call in the previous month. There was a high prevalence of on-call work in younger respondents (63.1% of participants aged 18–24 years), and those who worked multiple jobs and more weekly work hours. Additionally, high prevalence rates of on-call work were reported by machinery operators, drivers, community and personal service workers, sales workers, and high-level managers. Conclusions These data suggest that on-call work is more prevalent than previously recorded and is likely to refer to a broad set of employment arrangements. Current classification systems may therefore be inadequate for population-level research. A taxonomy for the classification of on-call work is proposed, incorporating traditional on-call work, gig economy work, relief, or unscheduled work, and out of hours work.

scholarly journals INTRA- AND INTER-OBSERVER AGREEMENT IN THE AO AND GARNAVOS SYSTEMS FOR DIAPHYSEAL HUMERUS FRACTURE

2017 ◽  
Vol 25 (4) ◽  
pp. 159-161 ◽  
Author(s):  
Roberto Meriqui Neto ◽  
Rodrigo Yuzo Masuda ◽  
Artur Yudi Utino ◽  
Rafael Pierami ◽  
Fábio Teruo Matsunaga ◽  
...  
Keyword(s):  
Classification Systems ◽  
Adult Patients ◽  
Observer Agreement ◽  
Humerus Fracture ◽  
Radiology Department ◽  
Level Of Evidence ◽  
X Ray ◽  
Orthopedic Surgeons ◽  
High Level ◽  
Humeral Diaphysis

ABSTRACT Objective: The objective of this study was to compare inter- and intra-observer agreement using the Garnavos and AO/ASIF systems for classifying humeral diaphysis fractures . Methods: Eighty X-ray images taken of humeral diaphysis fractures in adult patients (age≥18 years) between January 2013 and September 2015 in the Radiology Department of Hospital São Paulo were selected for subsequent classification by five orthopedic surgeons with differing levels of experience. The images were examined at two different times and reproducibility analysis was evaluated using Fleiss’ kappa to verify intra- and inter-observer agreement . Results: High-level agreement was observed for both classification systems, but particularly for the AO/ASIF classification. Inter-observer evaluation yielded excellent levels of agreement for both classifications, but principally for the Garnavos classification . Conclusions: Good or excellent inter- and intra-observer agreement was seen for both the AO/ASIF and Garnavos classification systems. However, intra-observer agreement was higher for the AO/ASIF system and inter-observer agreement was higher for the Garnavos classification. Level of Evidence II, Diagnostic Studies - Investigating a Diagnostic Examination.

A FPGA CORE GENERATOR FOR EMBEDDED CLASSIFICATION SYSTEMS

2011 ◽  
Vol 20 (02) ◽  
pp. 263-282 ◽  
Author(s):  
DAVIDE ANGUITA ◽  
LUCA CARLINO ◽  
ALESSANDRO GHIO ◽  
SANDRO RIDELLA
Keyword(s):  
Pattern Recognition ◽  
Vision System ◽  
Classification Systems ◽  
Support Vector ◽  
Digital Architecture ◽  
Current State ◽  
Field Programmable ◽  
Hardware Description ◽  
High Level ◽  
Core Description

We describe in this work a Core Generator for Pattern Recognition tasks. This tool is able to generate, according to user requirements, the hardware description of a digital architecture, which implements a Support Vector Machine, one of the current state-of-the-art algorithms for Pattern Recognition. The output of the Core Generator consists of a high-level language hardware core description, suitable to be mapped on a reconfigurable device, like a Field Programmable Gate Array (FPGA). As an example of the use of our tool, we compare different solutions, by targeting several reconfigurable devices, and implement the recognition part of a machine vision system for automotive applications.

Nomenclature and systems of classification for cardiomyopathy in children

2015 ◽  
Vol 25 (S2) ◽  
pp. 31-42 ◽  
Author(s):  
Laura Konta ◽  
Rodney C. G. Franklin ◽  
Juan P. Kaski
Keyword(s):  
Heart Association ◽  
World Health Organisation ◽  
Genetic Mutation ◽  
Classification Systems ◽  
World Health ◽  
Recent Attempt ◽  
Systemic Involvement ◽  
Organ Systems ◽  
European Society Of Cardiology ◽  
High Level

AbstractThere has been a progressive evolution in systems of classification for cardiomyopathy, driven by advances in imaging modalities, disease recognition, and genetics, following initial clinical descriptions in the 1960s. A pathophysiological classification emerged and was endorsed by World Health Organisation Task Forces in 1980 and 1995: dilated, hypertrophic, restrictive, and arrhythmogenic right ventricular cardiomyopathies; subdivided into idiopathic and disease-specific cardiomyopathies. Genetic advances have increasingly linked “idiopathic” phenotypes to specific mutations, although most linkages exhibit highly variable or little genotype–phenotype correlation, confounded by age-dependent changes and varying penetrance. The following two dominant classification systems are currently in use, with advocates in both continents. First, American Heart Association (2006): “A heterogeneous group of diseases of the myocardium associated with mechanical and/or electrical dysfunction that usually exhibit inappropriate ventricular hypertrophy or dilatation due to a variety of causes that frequently are genetic”. These are subdivided to those predominantly involving the heart – primary – due to genetic mutation, including ion channelopathies, acquired disease, or mixed; and those with systemic involvement in other organ systems – secondary. Second, European Society of Cardiology (2008): “A myocardial disorder in which heart muscle is structurally and functionally abnormal… sufficient to cause the observed myocardial abnormality”, with subdivision to familial and non-familial, excluding ion channelopathies, and split to specific disease subtypes and idiopathic. Further differences exist in the definitions for hypertrophic cardiomyopathy; however, whichever high-level classification is used, the clinical reality remains phenotype driven. Clinical evaluation and diagnostic imaging dominate initial patient contact, revealing diagnostic red flags that determine further specific tests. Genetic testing is undertaken early. A recent attempt to harmonise these competing systems named the MOGE(S) system, based on descriptive logical nosology, currently remains unproven as a fully practical solution.

scholarly journals Defining Uncertainty: Comparing Resource/Reserve Classification Systems for Coal and Coal Seam Gas

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6245
Author(s):  
Tim Moore ◽  
Mike Friederich
Keyword(s):  
Coal Seam ◽  
Oil And Gas ◽  
Mineral Resources ◽  
Classification Systems ◽  
Coal Seam Gas ◽  
Mining Investment ◽  
Petroleum Resource ◽  
High Level ◽  
Chinese Standard

Transparent, objective, and repeatable resource assessments should be the goal of companies, investors, and regulators. Different types of resources, however, may require different approaches for their quantification. In particular, coal can be treated both as a solid resource (and thus be mined) as well as a reservoir for gas (which is extracted). In coal mining, investment decisions are made based on a high level of data and establishment of seam continuity and character. The Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (the JORC Code) allows deposits to be characterised based on the level of geological and commercial certainty. Similarly, the guidelines of the Petroleum Resource Management System (PRMS) can be applied to coal seam gas (CSG) deposits to define the uncertainty and chance of commercialisation. Although coal and CSG represent two very different states of resources (i.e., solid vs. gaseous), their categorisation in the JORC Code and PRMS is remarkably similar at a high level. Both classifications have two major divisions: resource vs. reserve. Generally, in either system, resources are considered to have potential for eventual commercial production, but this has not yet been confirmed. Reserves in either system are considered commercial, but uncertainty is still denoted through different subdivisions. Other classification systems that can be applied to CSG also exist, for example the Canadian Oil and Gas Evaluation Handbook (COGEH) and the Chinese Standard (DZ/T 0216-2020) and both have similar high-level divisions to the JORC Code and PRMS. A hypothetical case study of a single area using the JORC Code to classify the coal and PRMS for the gas showed that the two methodologies will have overlapping, though not necessarily aligned, resource and reserve categories.

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