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Predictive queries on moving objects databases / (Record no. 78892)

MARC details
000 -LEADER
fixed length control field 03233cam a2200337 a 4500
003 - CONTROL NUMBER IDENTIFIER
control field EG-GiCUC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250223032634.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 201122s2020 ua d f m 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency EG-GiCUC
Language of cataloging eng
Transcribing agency EG-GiCUC
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title eng
049 ## - LOCAL HOLDINGS (OCLC)
Holding library Deposite
097 ## - Thesis Degree
Thesis Level Ph.D
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number Cai01.20.04.Ph.D.2020.Mo.P
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Mohammed Abdalla Mahmoud Youssif
245 10 - TITLE STATEMENT
Title Predictive queries on moving objects databases /
Statement of responsibility, etc. Mohammed Abdalla Mahmoud Youssif ; Supervised Hoda Mokhtar Omar Mokhtar , Neveen Elgamal
246 15 - VARYING FORM OF TITLE
Title proper/short title الاستعلامات التنبؤية على قاعدة بيانات الكائنات المتحركة
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Cairo :
Name of publisher, distributor, etc. Mohammed Abdalla Mahmoud Youssif ,
Date of publication, distribution, etc. 2020
300 ## - PHYSICAL DESCRIPTION
Extent 80 Leaves :
Other physical details charts ;
Dimensions 30cm
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Ph.D.) - Cairo University - Faculty of Computers and Artificial Intelligenc - Department of Information Systems
520 ## - SUMMARY, ETC.
Summary, etc. Future trajectory prediction for moving objects, e.g., vehicles, has a significant impact on many location-based services such as location-aware search, traffic management, mobile advertising, and travel guidance. The existing techniques which predict the future path(s) of moving objects depend mainly on their motions history to perform the prediction process. As a result, these techniques fail when moving objects{u2019} history is unavailable. This thesis aims to present efficient solutions for predicting the trajectories of moving objects without relying on their past trajectories. The proposed solutions include - (1) SimilarMove: a similarity-based prediction system for moving object future path, (2) DeepMotions: a deep learning system for moving object future path prediction, and (3) SAM: a spatial attention model for future trajectory prediction.The main idea of SimilarMove is obtaining the future paths of the query moving object in terms of other objects currently moving similar to the query object. After that, SimilarMove employs a Hidden Markov Model that receive these similar trajectories as an input and generates the possible future paths with their related probabilities as an output.The DeepMotions extracts the latent motion patterns from K nearest neighbor similar objects moving like the query moving object. Then, a Bi-directional recurrent deep-learning model is built based on these extracted motions and generate predictions. The main idea of SAM is to generate predictions by not scanning the whole input trajectory sequence but, focuses only on the significant positions of the input trajectory sequences to produce the output. This allows the internal representation of input trajectories to be refined based on the relevant information from the query object. Then, by gathering relevant information into the final representation, only the necessary information is provided to predict the final answer of the query object
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Issued also as CD
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Moving objects databases
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Predictive queries
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term SAM
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Hoda Mokhtar Omar Mokhtar ,
Relator term
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Neveen Elgamal ,
Relator term
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://172.23.153.220/th.pdf">http://172.23.153.220/th.pdf</a>
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN)
Cataloger Nazla
Reviser Revisor
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN)
Cataloger Shimaa
Reviser Cataloger
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Thesis
Holdings
Source of classification or shelving scheme Not for loan Home library Current library Date acquired Full call number Barcode Date last seen Koha item type Copy number
Dewey Decimal Classification   المكتبة المركزبة الجديدة - جامعة القاهرة قاعة الرسائل الجامعية - الدور الاول 11.02.2024 Cai01.20.04.Ph.D.2020.Mo.P 01010110082116000 22.09.2023 Thesis  
Dewey Decimal Classification   المكتبة المركزبة الجديدة - جامعة القاهرة مخـــزن الرســائل الجـــامعية - البدروم 11.02.2024 Cai01.20.04.Ph.D.2020.Mo.P 01020110082116000 22.09.2023 CD - Rom 82116.CD