Mega-Precovery, a dedicated project for data mining worldwide image archives for poorly known asteroids Marcel Popescu Membru Astroclub Bucuresti Colaborator.

Slides:



Advertisements
Similar presentations
How to Set Up a System for Teaching Files, Conferences, and Clinical Trials Medical Imaging Resource Center.
Advertisements

Kyoto Interop meeting, 17 May A VOTable application: Solar System objects in the VO J. Berthier 1, F. Vachier 1, V. Lainey 1, W. Thuillot 1, J.-E.
1 CSIS 7102 Spring 2004 Lecture 9: Recovery (approaches) Dr. King-Ip Lin.
Poor Mans Cluster (PMC) Johny Balian. Outline What is PMC How it works Concept Positive aspects Negative aspects Good and Bad Application ideas Monte.
MOST - Moving Object Search Tool for NEOWISE and IRSA Kevin Yau 6/11/2010.
CADDLAB Medical Imaging on Remote Compute Servers.
Interpret Application Specifications
Copyright © 2006 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill Technology Education Copyright © 2006 by The McGraw-Hill Companies,
PubMed/How to Search, Display, Download & (module 4.1)
Supporting the Automatic Construction of Entity Aware Search Engines Lorenzo Blanco, Valter Crescenzi, Paolo Merialdo, Paolo Papotti Dipartimento di Informatica.
1 A web enabled compact flash card reader eeble. 2 Weeble Team Chris Foster Nicole DiGrazia Mike Kacirek Website
CSI315CSI315 Web Development Technologies Continued.
1 EURONEAR, an international project to study Near Earth Asteroids Ovidiu Vaduvescu Conferinta Diasporei - Workshop Astronomie Sep 2010 Bucharest,
Web Search Created by Ejaj Ahamed. What is web?  The World Wide Web began in 1989 at the CERN Particle Physics Lab in Switzerland. The Web did not gain.
CS621 : Seminar-2008 DEEP WEB Shubhangi Agrawal ( )‏ Jayalekshmy S. Nair ( )‏
Blooms’ Taxonmy Learning Theories PBL and Hardware.
Unit 3 – Information Systems
IBrutus Request Processor Grammar Rules Computer Vision Module Software Analysis and Design  Multiple data sources - CETI project data is spread over.
Chapter 7 Web Content Mining Xxxxxx. Introduction Web-content mining techniques are used to discover useful information from content on the web – textual.
A Metadata Catalog Service for Data Intensive Applications Presented by Chin-Yi Tsai.
Animation of Sequential Images …through ImageJ. Background ImageJ A cross-platform public domain image processing software that had been developed in.
Pi In The Sky (Web Interface) Gaston Seneza Philander Smith College, Little Rock, AR SIParCS Intern Mentors: Dr. Richard Loft & Dr. Raghu Raj Kumar 1.
Introduction to Apache OODT Yang Li Mar 9, What is OODT Object Oriented Data Technology Science data management Archiving Systems that span scientific.
Embedded Multicore processing for Mobile Communications Real-time Contracts and Thread Profiling York Jack Whitham.
University Of Palestine. Department of Information Technology.
Similar Document Retrieval and Analysis in Information Retrieval System based on correlation method for full text indexing.
HW#2: A Strategy for Mining Association Rules Continuously in POS Scanner Data.
Biomechanical Integration of Essential Human Movement Parameters By Gideon Ariel, Alfred Finch and Ann Penny.
2007. Software Engineering Laboratory, School of Computer Science S E Web-Harvest Web-Harvest: Open Source Web Data Extraction tool 이재정 Software Engineering.
DATABASE MANAGEMENT SYSTEMS CMAM301. Introduction to database management systems  What is Database?  What is Database Systems?  Types of Database.
1 Computing Challenges for the Square Kilometre Array Mathai Joseph & Harrick Vin Tata Research Development & Design Centre Pune, India CHEP Mumbai 16.
Attack signatures derived from Metasploit Final Presentation E. Ramirez A. Zoghbi
Component 4: Introduction to Information and Computer Science Unit 6a Databases and SQL.
IDigBio is funded by a grant from the National Science Foundation’s Advancing Digitization of Biodiversity Collections Program (Cooperative Agreement EF ).
Data Mining for Near Earth Asteroids in the EuroNear Project.
Utilizing Databases to Manage Precision Ag Data Candice Johnson BAE 4213 Spring 2004.
Lesson 2: The World Wide Web Objectives After completing this lesson, you will be able to:  Define WWW and its relation to the Internet.  Explain how.
Implementation of a Relational Database as an Aid to Automatic Target Recognition Christopher C. Frost Computer Science Mentor: Steven Vanstone.
How to Set Up a System for Teaching Files, Conferences, and Clinical Trials Medical Imaging Resource Center.
Web Design and Development. World Wide Web  World Wide Web (WWW or W3), collection of globally distributed text and multimedia documents and files 
1 Introduction to Data Mining C hapter 1. 2 Chapter 1 Outline Chapter 1 Outline – Background –Information is Power –Knowledge is Power –Data Mining.
Big traffic data processing framework for intelligent monitoring and recording systems 學生 : 賴弘偉 教授 : 許毅然 作者 : Yingjie Xia a, JinlongChen a,b,n, XindaiLu.
GEO Online Detector Characterization System R. Balasubramanian Cardiff University LSC March 2003 LIGO-G Z.
AHM04: Sep 2004 Nottingham CCLRC e-Science Centre eMinerals: Environment from the Molecular Level Managing simulation data Lisa Blanshard e- Science Data.
Copyright 2007, Information Builders. Slide 1 iWay Web Services and WebFOCUS Consumption Michael Florkowski Information Builders.
GROUP PresentsPresents. WEB CRAWLER A visualization of links in the World Wide Web Software Engineering C Semester Two Massey University - Palmerston.
Web Design Terminology Unit 2 STEM. 1. Accessibility – a web page or site that address the users limitations or disabilities 2. Active server page (ASP)
Cyber Community Centre in Kg. Menjelin Prepared By: Muhammad Zulhilmi Bin Halim ( ) Mohammad Solihin Bin Abdul Rahman ( ) Fawwaz Bin Mohd.
General Architecture of Retrieval Systems 1Adrienn Skrop.
June 12, 2016CITALA'121 Cloud Computing Technology For Large Scale and Efficient Arabic Handwriting Recognition System HAMDI Hassen, KHEMAKHEM Maher
VIEWS b.ppt-1 Managing Intelligent Decision Support Networks in Biosurveillance PHIN 2008, Session G1, August 27, 2008 Mohammad Hashemian, MS, Zaruhi.
ACES User Interface Workshop #1 Prototype Inspection 22. November 2011.
MIRC Overview Medical Imaging Resource Center John Perry RSNA 2009.
6/28/ A global mesh of interconnected networks (internetworks) meets these human communication needs. Some of these interconnected networks are.
Lecture-6 Bscshelp.com. Todays Lecture  Which Kinds of Applications Are Targeted?  Business intelligence  Search engines.
A Semi-Automated Digital Preservation System based on Semantic Web Services Jane Hunter Sharmin Choudhury DSTC PTY LTD, Brisbane, Australia Slides by Ananta.
1 Software complex “Asteroids and Comets” at the site of Institute of Applied Astronomy RAS N. B. Zheleznov, O. M. Kochetova, Yu. S. Bondarenko, Yu. A.
Data mining in web applications
Creighton Barrett Dalhousie University Archives
Introduction to Computing Lecture # 13
SEARCH ENGINES & WEB CRAWLER Akshay Ghadge Roll No: 107.
System Design.
Configuration for Network Security
“Using Computer Technology to Overcome Bottlenecks in the Forensic DNA Testing Process and Improve Data Recovery from Complex Samples”
Information Technology Fundamentals
Manuscript Transcription Assistant Initiative
Web Mining Department of Computer Science and Engg.
Data Mining (Don’t worry, I am not presenting these slides; just for your reading pleasure)
Databases and Information Systems
Expert Knowledge Based Systems
Presentation transcript:

Mega-Precovery, a dedicated project for data mining worldwide image archives for poorly known asteroids Marcel Popescu Membru Astroclub Bucuresti Colaborator EURONEAR

Abstract. We describe our software which perform a search for images that contains asteroids in a Mega-Archive – a database containing observations logs from world wide. This database is flexible allowing other observations logs from different archives to be added. Both "precoveries" (apparitions before discovery date) and "recoveries" (apparitions after discovery date) are reported. Using the Internet, this facility will be available to the whole astronomical community willing to study image archives that contain information about different asteroids of interests. This presentation is organized as fallow: -> Introduction ->The idea behind Mega-Precovery; -> The format of the Mega-Archive; -> Schematic of the algorithm; -> Performances and test runs; -> Conclusions and further improvements

Introduction The vast collection of image archives stored worldwide is still insufficiently explored and could be mined for asteroids appearing occasionally in their fields. Both precovered and recovered objects can be measured, allowing an improve of orbit calculation and other studies like dynamical investigations or predictions of future close approach to the Earth. Searches of this image archives for this objects is therefore highly desirable and are important resources in studies of asteroids.

Basically, intended to be used for poorly known asteroids or newly discovered asteroids, but can be used for any asteroid. We start the database called – Mega-Archive with the observations logs from ESO/WFI, ING/INT, CFHTLS. For this purpose we designed Mega–Precovery, a PHP software, which continues some of the ideas of Precovery. The search is performed over a very-large database of pointings logs. The Mega-Archive want to become “open project” allowing other observations logs to be added for exploration.

The ideas behind Mega-Precovery Basically we continue the ideas of Precovery: search for asteroids imaged in a archive of images or photographic plates.

The main differences are: -> the size of the database: Mega-Archive contain until now ~ pointings logs. -> this software is focused on the asteroid of interest and basically intended to be used for poorly know asteroids and for important asteroids like PHA (potentially hazardous asteroids) and (VI) Virtual Impactors. ->Mega-Archive will be flexible allowing other archives to be added(we hope to reach 1M of logs for justifying the name). ->the software receive as input a list of the name of the asteroids for which a precovery/recovery is desired. At the output the software will return a list with the name of images found in Mega-Archive (or just in selected archives) with the required asteroids in the field.

The format of the Mega-Archive In order to perform the search we need the following information stored in Mega-Archive for each available image: -> name of the image in the specific archive; -> center of the field: * RA[h] * DEC[ ° ] -> Julian Day for observation; -> Field Magnification; We chose the format of INT observations logs for this database: “ Image name|Julian Day|Exposure time|RA|DEC|Field Magnification| Field Magnification| Filter ” *The archives with different observations logs were in different format. For this, additional software was made to transform them in format described above.

Archives included until now in the MegaArchive: - ING/INT(~ imags); - ESO/MPG(~ imags); - CFHTLS(~ imags): *CFHTLS-Deep; *CFHTLS-Wide; *CFHTLS-VeryWide; Archives that we hope to include soon in MegaArchive : - WFPDB – Sofia; - AIRA; - Subaru

Schematic of the project Input: File with names of the asteroids, one per raw; Output: File with the names of the images (pointings) that contain in the field the desired asteroid; Additional files used (files stored on server): → astorb.dat (downloaded from ) → Mega - Archive Files:

Schematic of the project: - the main components are: Mega- Archive, astorb.dat, MegaPrecovery, query to Ephemerides Server (IMCCE);

Performances and test runs Test version, running on a PC with a processor with frequency 1.8GHz, and Internet connection speed 54 Mbps; 25~45s for images searched in ESO logs archive (~0.1M pointings), for one input object. The time to run the program, depends on the number of the inputs. Desirable to submit small files (5-50 objects); The time of run for one object depends on the number of occurrences found;

Conclusions There is a huge amount of information stored in images and wide field plates archives around the world, insufficiently explored. This information could be very useful when computing the orbits and dynamical characteristics of poorly known asteroids or newly discovered asteroids. With the purpose to explore this information we created Mega- Precovery, a public facility which will be integrated in the EURONEAR project. The software, which can be launch from the EURONEAR website requires as input the name of the object/objects and performs a search in the entire Mega-Archive(or in selected archives) and gives as output the observation logs for the images that have in the field asteroid/asteroids. This presentation described the Mega-Precovery facility which include the software and database.