scholarly journals LEDA — A Library of Efficient Data Types and Algorithms

1992 ◽  
pp. 105-108
Author(s):  
Stefan Näher ◽  
Kurt Mehlhorn
Keyword(s):  
Data Types ◽  
Efficient Data

scholarly journals TaxonWorks: An experience of migrating large datasets into the new cybertaxonomic infrastructure

2019 ◽  
Vol 3 ◽  
Author(s):  
Dmitry Dmitriev
Keyword(s):  
Web Application ◽  
Data Entry ◽  
Large Datasets ◽  
Character Trait ◽  
Data Migration ◽  
Data Types ◽  
Web Interfaces ◽  
Illinois Natural History Survey ◽  
Efficient Data ◽  
History Survey

TaxonWorks (http://taxonworks.org) in an integrated, open-source, cybertaxonomic web application serving taxonomists and biodiversity scientists. It is designed to facilitate efficient data capture, storage, manipulation, and retrieval. It integrates a wide variety of data types used by biodiversity scientists, including, but not limited to, taxonomy (with validation based on codes of zoological, botanical, bacterial, and viral nomenclature), specimen data, bibliographies, media (images, PDFs, sounds, videos), morphology (character/trait matrices), distribution, biological associations. Available TaxonWorks web interfaces currently provide various data entry forms for simple and advanced querying of the database. TaxonWorks has integrated batch uploader functionality. But, for larger datasets, specialized migration scripts were used. Several projects, historically build in 3i (http://dmitriev.speciesfile.org), MX (http://mx.phenomix.org), SpeciesFiles (http://software.speciesfile.org), and other databases, have been or are being migrated into TaxonWorks. Of the projects moving into TaxonWorks, it is worth mentioning several: 3i World Auchenorrhyncha Database, LepIndex, Universal Chalcidoidea Database, Orthoptera SpeciesFile, Plecoptera SpeciesFile, Illinois Natural History Survey Insect Collection database, and several others. An experience of the data migration will be shared during the presentation.

scholarly journals Efficient Data Streaming Multiway Aggregation through Concurrent Algorithmic Designs and New Abstract Data Types

2017 ◽  
Vol 4 (2) ◽  
pp. 1-28 ◽  
Author(s):  
Vincenzo Gulisano ◽  
Yiannis Nikolakopoulos ◽  
Daniel Cederman ◽  
Marina Papatriantafilou ◽  
Philippas Tsigas
Keyword(s):  
Data Streaming ◽  
Abstract Data Types ◽  
Data Types ◽  
Efficient Data ◽  
Abstract Data

IoT based e-Healthcare System to Enable Remote Patient Care based on Cloud Server

2017 ◽  
Vol 7 (7) ◽  
pp. 36
Author(s):  
P.Venu Gopala Rao ◽  
Eslavath Raja ◽  
Ramakrishna Gandi ◽  
G. Ravi Kumar
Keyword(s):  
Low Cost ◽  
Vital Signs ◽  
Smart Phone ◽  
Medical Professional ◽  
Design Parameters ◽  
Cloud Server ◽  
Significant Area ◽  
Efficient Data ◽  
System Data ◽  
Remote Patient

IoT (Internet of Things) has become most significant area of research to design an efficient data enabled services with the help of sensors. In this paper, a low-cost system design for e-healthcare service to process the sensitive health data is presented. Vital signs of the human body are measured from the patient location and shared with a registered medical professional for consultation. Temperature and heart rate are the major signals obtained from a patient for the initial build of the system. Data is sent to a cloud server where processing and analysis is provided for the medical professional to analyze. Secure transmission and dissemination of data through the cloud server is provided with an authentication system and the patient could be able to track his data through a smart phone on connecting to the cloud server. A prototype of the system along with its design parameters has been discussed.

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