scholarly journals Data Structure Comparison Between MySql Relational Database and Firebase Database NoSql on Mobile Based Tourist Tracking Application

2020 ◽  
Vol 1569 ◽  
pp. 032092
Author(s):  
I K G Sudiartha ◽  
I N E Indrayana ◽  
I W Suasnawa ◽  
S A Asri ◽  
Putu Wijaya Sunu
Keyword(s):  
Data Structure ◽  
Relational Database ◽  
Structure Comparison

scholarly journals Operatic Productions in the Netherlands, 1886–1995: from Printed Annals to Searchable Performance Data

2020 ◽  
Vol 5 (2) ◽  
pp. 79-90
Author(s):  
Mascha M. van Nieuwkerk ◽  
Liselotte Salters ◽  
R. M. Helmers ◽  
Ivan Kisjes
Keyword(s):  
Data Structure ◽  
The Netherlands ◽  
Relational Database ◽  
Performing Arts ◽  
Relevant Information ◽  
Performance Data ◽  
Original Publication ◽  
Performance History ◽  
History Of ◽  
Opera Productions

Abstract This data paper accompanies the database Operatic productions in the Netherlands, an open dataset containing details on over five thousand opera productions in the Netherlands between 1885 and 1995 extracted from the Annalen van de Nederlandse Opera-gezelschappen (Annals of the Opera Companies in the Netherlands), which appeared in book form in 1996. These data give an extremely rich account of the performance history of operatic works and the personnel involved in their production. Since the original publication lacks a critical introduction, the authors have attempted to reconstruct the origins and systematics of the collection. They also discuss the attributes of the data and the basic data structure in order to give users relevant information to use and restructure the data for their interests. The data structure and metadata classifications are based on an inventory of the classifications used in existing performing arts databases across Europe. This facilitates future connections to other relevant performing arts datasets. The transfer of the Annals into a relational database finally brings out their full research potential.

scholarly journals System for Identifying Pests and Diseases in Soybean Crop through Natural Language Processing

2022 ◽  
Vol 29 (1) ◽  
pp. 28-41
Author(s):  
Carolinne Roque e Faria ◽  
Cinthyan S. C. Barbosa
Keyword(s):  
Natural Language Processing ◽  
Data Structure ◽  
Natural Language ◽  
Computer System ◽  
Language Processing ◽  
Relational Database ◽  
Soybean Cultivar ◽  
Soybean Crop ◽  
Pests And Diseases ◽  
Processing Techniques

The presence of technologies in the agronomic field has the purpose of proposing the best solutions to the challenges found in agriculture, especially to the problems that affect cultivars. One of the obstacles found is to apply the use of your own language in applications that interact with the user in Brazilian Agribusiness. Therefore, this work uses Natural Language Processing techniques for the development of an automatic and effective computer system to interact with the user and assist in the identification of pests and diseases in soybean crop, stored in a non-relational database repository to provide accurate diagnostics to simplify the work of the farmer and the agricultural stakeholders who deal with a lot of information. In order to build dialogues and provide rich consultations, from agriculture manuals, a data structure with 108 pests and diseases with their information on the soybean cultivar and through the spaCy tool, it was possible to pre-process the texts, recognize the entities and support the requirements for the development of the conversacional system.

scholarly journals Reflections on the Intermediate Data Structure (IDS)

2021 ◽  
Vol 10 ◽  
pp. 71-75
Author(s):  
George Alter
Keyword(s):  
Data Structure ◽  
Life Course ◽  
Data Structures ◽  
Relational Database ◽  
Life Histories ◽  
Social Scientists ◽  
Database Model ◽  
Intermediate Data ◽  
Value Model ◽  
Historical Life

The Intermediate Data Structure (IDS) encourages sharing historical life course data by storing data in a common format. To encompass the complexity of life histories, IDS relies on data structures that are unfamiliar to most social scientists. This article examines four features of IDS that make it flexible and expandable: the Entity-Attribute-Value model, the relational database model, embedded metadata, and the Chronicle file. I also consider IDS from the perspective of current discussions about sharing data across scientific domains. We can find parallels to IDS in other fields that may lead to future innovations.

scholarly journals Perbandingan Antara SQLite, Room, dan RBDLiTe Dalam Pembuatan Basis Data pada Aplikasi Android

2020 ◽  
Vol 7 (3) ◽  
pp. 376
Author(s):  
Raden Bagus Dimas Putra ◽  
Eko Setia Budi ◽  
Abdul Rahman Kadafi
Keyword(s):  
Operating System ◽  
Data Structure ◽  
Relational Database ◽  
Program Code ◽  
Entire Data ◽  
Android Applications ◽  
The Common ◽  
Internal Database ◽  
Market Needs

Android is one of the largest mobile operating system platforms today. Amid the ever-increasing needs of users, Android programmers are still lacking to meet the current market needs. One of the problems that causes this is the difficulty of creating an internal database, so many people give up to learn to make Android applications. Android's internal database is hard to create because the entire data structure on that database should be built with the query executed in the created program code. Some of the common internal databases currently used are SQLiTe and Room. Both databases are quite difficult to learn where SQLite should build everything from scratch while Room should study the structure and systematics of of the library. Therefore, in this article, the author proposes library and template named "Relational Database Library and Template" which will be referred to as RBDLiTe which can create an internal database for Android applications easily which will also be compared with SQLiTe and Room in its use.

scholarly journals Fast Image Index for Database Management Engines

2020 ◽  
Vol 10 (2) ◽  
pp. 113-123 ◽  
Author(s):  
Rafał Grycuk ◽  
Patryk Najgebauer ◽  
Miroslaw Kordos ◽  
Magdalena M. Scherer ◽  
Alina Marchlewska
Keyword(s):  
Data Structure ◽  
Relational Database ◽  
Database Management ◽  
Large Scale ◽  
Local Features ◽  
Database Management Systems ◽  
Local Feature ◽  
Management Systems ◽  
Image Descriptor ◽  
Benchmark Datasets

AbstractLarge-scale image repositories are challenging to perform queries based on the content of the images. The paper proposes a novel, nested-dictionary data structure for indexing image local features. The method transforms image local feature vectors into two-level hashes and builds an index of the content of the images in the database. The algorithm can be used in database management systems. We implemented it with an example image descriptor and deployed in a relational database. We performed the experiments on two image large benchmark datasets.

Sign in / Sign up

Export Citation Format

Share Document