Data Retrieval System of JMA Analog Seismograms in the Headquarters for Earthquake Research Promotion of the Japanese Government

2020 ◽  
Vol 91 (3) ◽  
pp. 1403-1412 ◽  
Author(s):  
Mitsuko Furumura ◽  
Koji Iwasa ◽  
Yasunori Suzuki ◽  
Tomotsugu Demachi ◽  
Takeo Ishibe ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Image Recognition ◽  
Technological Progress ◽  
Retrieval System ◽  
Digital Images ◽  
Data Retrieval ◽  
Japanese Government ◽  
Japan Meteorological Agency ◽  
Earthquake Research ◽  
Research Promotion

Abstract To archive precious analog seismograms of major earthquakes that occurred in and around Japan, we have scanned selected analog seismograms from 113 stations deployed by the Japan Meteorological Agency (JMA) and are constructing a database of the scanned digital images accessible through the website of the Headquarters for Earthquake Research Promotion (HERP) of the Japanese government. This project started in 2006 and was conducted by the Association for the Development of Earthquake Prediction. The database of HERP now contains more than 185,000 digital images of seismograms recorded during the period from 1884 to 1995. It includes seismograms of earthquakes that occurred in and around Japan and of some major teleseismic earthquakes. The oldest analog seismogram was recorded on 2 January 1884 at a station in Tokyo. The seismograms are the intellectual property of mankind, and the database of these digital images will be an important material for studies of past destructive earthquakes. Technological progress such as artificial intelligence image recognition technology will help to further explore the data.

ASPECTS REGARDING THE USE OF ARTIFICIAL INTELLIGENCE IN IMPROVING DEFENSE RESOURCE MANAGEMENT

2021 ◽  
Vol 17 (1) ◽  
pp. 323-330
Author(s):  
Gabriela-Florina NICOARĂ ◽  
Gergonia-Cristiana BOGĂȚEANU
Keyword(s):  
Artificial Intelligence ◽  
Resource Management ◽  
Technological Progress ◽  
Digital Systems ◽  
Constructive Approach ◽  
The Past ◽  
A Priority ◽  
High Level

Abstract: Regarding the society evolution dominated by a high-level technology, we consider this article a constructive approach. The aim of the paper is to highlight a few activities/places/spots in which competences of humans/soldiers interfere with different elements of the artificial intelligence. We deem that the technological progress in the past few years has been impressive. Nowadays, thousands of activities that were mostly or exclusively executed by people can be done faster and often with greater precision using digital systems. In this instance and considering the achievement of functional compatibility between Romanian Army and forces from NATO as being a priority, the development of the technology based on artificial intelligence is vital within the defense resource management.

scholarly journals Development of parser agents for bibliographic data retrieval

2018 ◽  
Vol 33 (4) ◽  
Author(s):  
Murari Kumar ◽  
Samir Farooqi ◽  
K. K. Chaturvedi ◽  
Chandan Kumar Deb ◽  
Pankaj Das
Keyword(s):  
Retrieval System ◽  
Data Retrieval ◽  
Web Pages ◽  
Bibliographic Database ◽  
Bibliographic Information ◽  
Open Access Journals ◽  
Bibliographic Records ◽  
Bibliographic Data ◽  
Structured Information ◽  
The Web

Bibliographic data contains necessary information about literature to help users to recognize and retrieve that resource. These data are used quantitatively by a “Bibliometrician” for analysis and dissemination purpose but with the increasing rate of literature publication in open access journals such as Nucleic Acids Research (NAR), Springer, Oxford Journals etc., it has become difficult to retrieve structured bibliographic information in desired format. A digital bibliographic database contains necessary and structured information about published literature. Bibliographic records of different articles are scattered and resides on different web pages. This thesis presents the retrieval system for bibliographic data of NAR at a single place. For this purpose, parser agents have been developed which access the web pages of NAR and parse the scattered bibliographic data and finally store it into a local bibliographic database. Based on the bibliographic database, “three-tier architecture” has been utilized to display the bibliographic information in systematized format. Using this system, it would be possible to build the network between different authors and affiliations and also other analytical reports can be generated.

scholarly journals STATUS OF DATA RETRIEVAL SYSTEM AS OF APRIL 1, 1969

1969 ◽  
Author(s):  
R. L. Reynolds ◽  
R. L. Engel ◽  
R. T. Toyooka ◽  
E. L. Wells
Keyword(s):  
Retrieval System ◽  
Data Retrieval

scholarly journals Composite Materials Design Database and Data Retrieval System Requirements

1994 ◽  
Vol 116 (2) ◽  
pp. 531-538
Author(s):  
W. J. Rasdorf
Keyword(s):  
Composite Materials ◽  
Computer Technology ◽  
Retrieval System ◽  
Data Retrieval ◽  
Data Representation ◽  
Clear Understanding ◽  
Analysis And Design ◽  
Problems And Solutions ◽  
System Requirements ◽  
Design Software

Researchers and materials engineers require a greater understanding of the problems and solutions that emerge when integrating composite materials data with computer technology so that utilitarian composite materials databases can be developed to effectively and efficiently support analysis and design software. This paper primarily serves to analyze several of the problems facing developers of composite materials databases, evolving from the complexity of the materials themselves and from the current lack of testing and data representation standards. Without a clear understanding of the scope and nature of these problems, there is no possibility of designing concise yet comprehensive composites data models, yet we feel that such an understanding is presently lacking.

scholarly journals Application of Artificial Intelligence in Dynamic Image Recognition

2020 ◽  
Vol 1533 ◽  
pp. 032093
Author(s):  
Yonghua Hu ◽  
Dongning Yang ◽  
Zhisheng Zhang ◽  
Tianchun Yang ◽  
Junshu Peng
Keyword(s):  
Artificial Intelligence ◽  
Image Recognition ◽  
Dynamic Image

scholarly journals Research on Industrial Waste Recovery Network Optimization: Opportunities Brought by Artificial Intelligence

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Bin Liao ◽  
Ting Wang
Keyword(s):  
Artificial Intelligence ◽  
Environmental Pollution ◽  
Image Recognition ◽  
Network Optimization ◽  
Management System ◽  
Industrial Waste ◽  
Environmental Benefits ◽  
Waste Recovery ◽  
Industrial Parks ◽  
Urbanization In China

With the acceleration of industrialization and urbanization in China, a large amount of waste in industrial parks has become the main cause of regional environmental pollution. In order to solve this problem, this paper relied on artificial intelligence’s prediction technology and image recognition technology to intelligently upgrade the traditional industrial waste planning management system and designed a waste intelligent classification center with intelligent prediction and intelligent classification capabilities. So, as to realize this new intelligent classification center and explain its value, this paper explains the key implementation technology of this intelligent classification center and validates it by constructing a multitarget location model that considers both economic and environmental benefits.

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