scholarly journals INVESTIGATION OF METHODS AND ALGORITHMS OF MOVING OBJECT HASHING

2017 ◽  
Vol 2017 (1) ◽  
pp. 133-143
Author(s):  
Константин Гулаков ◽  
Konstantin Gulakov ◽  
Василий Гулаков ◽  
Vasiliy Gulakov ◽  
Юрий Сковородников ◽  
...  

The paper deals with the study of one of the urgent problems of real time applications in which objects have spatial and temporal dependences. With the development of wireless communication and position-ing technologies the problem of storage in a database and indexing a large quantity of moving objects becomes urgent. In this paper there is offered an idea based on the method of hashing allowing the consider-able decrease of the quantity of database updates and the fulfillment of an indexing procedure possible. The paper reports the following basic approaches to the solution of the problem mentioned: a hashing; LP-layer; a division of space into blocks; coverings be-tween blocks; the use of a dynamic update of blocks, and also combinations of approaches. In order to draw conclusions of efficiency of hash-functions offered there was carried out a work on the experimental assessment of methods mentioned. The results of the comparison of methods are presented according to different criteria: productivity, a quantity of database updates, amount of disk memory pages used. The conclusions and recommendations for use are formulated.


2016 ◽  
Vol 11 (4) ◽  
pp. 324
Author(s):  
Nor Nadirah Abdul Aziz ◽  
Yasir Mohd Mustafah ◽  
Amelia Wong Azman ◽  
Amir Akramin Shafie ◽  
Muhammad Izad Yusoff ◽  
...  


1989 ◽  
Author(s):  
Insup Lee ◽  
Susan Davidson ◽  
Victor Wolfe


2004 ◽  
Author(s):  
Alexandru Sheremet ◽  
Gregory W. Stone ◽  
James M. Kaihatu


2009 ◽  
Vol 18 (3-4) ◽  
pp. 47-54 ◽  
Author(s):  
J.J. Zenor ◽  
D.J. Murray-Smith ◽  
E.W. McGookin ◽  
R.E. Crosbie


Author(s):  
Mohsen Ansari ◽  
Amir Yeganeh-Khaksar ◽  
Sepideh Safari ◽  
Alireza Ejlali


Author(s):  
R.K. Clark ◽  
I.B. Greenberg ◽  
P.K. Boucher ◽  
T.F. Lunt ◽  
P.G. Neumann ◽  
...  


Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.



1989 ◽  
Vol 32 (7) ◽  
pp. 862-871 ◽  
Author(s):  
Clement Yu ◽  
Wei Sun ◽  
Dina Bitton ◽  
Qi Yang ◽  
Richard Bruno ◽  
...  


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