Safe locking policies for dynamic databases

Impact of long-term trials on crop production research and education

Acta Agronomica Hungarica ◽

10.1556/aagr.58.2010.suppl.1.1 ◽

2010 ◽

Vol 58 (Supplement 1) ◽

pp. 1-5 ◽

Cited By ~ 1

Author(s):

M. Jolánkai ◽

F. Nyárai ◽

K. Kassai

Keyword(s):

Crop Production ◽

Life Sciences ◽

Ecological Models ◽

Dynamic Databases ◽

Production Research ◽

Research And Education

Long-term trials have a twofold role in life sciences, acting as both live laboratories and public collections. Long-term trials are not simply scientific curios or the honoured relics of a museum, but highly valuable live ecological models that can never be replaced or restarted if once terminated or suspended. These trials provide valuable and dynamic databases for solving scientific problems. The present paper is intended to give a brief summary of the crop production aspects of long-term trials.

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The method of configuring dynamic databases

Information and Communication Technology for Education ◽

10.2495/icte130201 ◽

2014 ◽

Cited By ~ 6

Author(s):

Yuri Rogozov ◽

Alexander Sviridov ◽

Sergey Kucherov

Keyword(s):

Dynamic Databases

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Dynamic maintenance model for high average-utility pattern mining with deletion operation

Applied Intelligence ◽

10.1007/s10489-021-02539-4 ◽

2021 ◽

Author(s):

Jimmy Ming-Tai Wu ◽

Qian Teng ◽

Shahab Tayeb ◽

Jerry Chun-Wei Lin

Keyword(s):

Pattern Mining ◽

Computational Cost ◽

Practical Applications ◽

Itemset Mining ◽

Dynamic Databases ◽

Speed Up ◽

Dynamic Maintenance ◽

Average Utility ◽

High Utility ◽

Maintenance Model

AbstractThe high average-utility itemset mining (HAUIM) was established to provide a fair measure instead of genetic high-utility itemset mining (HUIM) for revealing the satisfied and interesting patterns. In practical applications, the database is dynamically changed when insertion/deletion operations are performed on databases. Several works were designed to handle the insertion process but fewer studies focused on processing the deletion process for knowledge maintenance. In this paper, we then develop a PRE-HAUI-DEL algorithm that utilizes the pre-large concept on HAUIM for handling transaction deletion in the dynamic databases. The pre-large concept is served as the buffer on HAUIM that reduces the number of database scans while the database is updated particularly in transaction deletion. Two upper-bound values are also established here to reduce the unpromising candidates early which can speed up the computational cost. From the experimental results, the designed PRE-HAUI-DEL algorithm is well performed compared to the Apriori-like model in terms of runtime, memory, and scalability in dynamic databases.

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IMIDB: An Algorithm for Indexed Mining of Incremental Databases

Journal of Intelligent Systems ◽

10.1515/jisys-2015-0107 ◽

2017 ◽

Vol 26 (1) ◽

pp. 69-85

Author(s):

Mohammed M. Fouad ◽

Mostafa G.M. Mostafa ◽

Abdulfattah S. Mashat ◽

Tarek F. Gharib

Keyword(s):

Data Structure ◽

Association Rules ◽

Efficient Algorithm ◽

Performance Comparison ◽

Incremental Mining ◽

Itemset Mining ◽

Large Databases ◽

Transactional Databases ◽

Dynamic Databases ◽

Database Size

AbstractAssociation rules provide important knowledge that can be extracted from transactional databases. Owing to the massive exchange of information nowadays, databases become dynamic and change rapidly and periodically: new transactions are added to the database and/or old transactions are updated or removed from the database. Incremental mining was introduced to overcome the problem of maintaining previously generated association rules in dynamic databases. In this paper, we propose an efficient algorithm (IMIDB) for incremental itemset mining in large databases. The algorithm utilizes the trie data structure for indexing dynamic database transactions. Performance comparison of the proposed algorithm to recently cited algorithms shows that a significant improvement of about two orders of magnitude is achieved by our algorithm. Also, the proposed algorithm exhibits linear scalability with respect to database size.

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MODELING OF DISTURBANCES IN STUDY OF CONTROL SYSTEMS

VESTNIK OF ASTRAKHAN STATE TECHNICAL UNIVERSITY SERIES MANAGEMENT COMPUTER SCIENCE AND INFORMATICS ◽

10.24143/2072-9502-2020-4-70-79 ◽

2020 ◽

Vol 2020 (4) ◽

pp. 70-79

Author(s):

Mikhail Vasilevich Lyakhovets ◽

Georgiy Valentinovich Makarov ◽

Alexandr Sergeevich Salamatin

Keyword(s):

Control Systems ◽

Generating Functions ◽

Special Functions ◽

Computer Training ◽

Full Scale ◽

Analytical Models ◽

Scale Model ◽

Data Series ◽

Dynamic Databases ◽

Natural Data

The article is devoted to questions of synthesis of full-scale - model realizations of data series on the basis of natural data for modeling of controllable and uncontrollable influences at research of operating and projected control systems, and also in training systems of computer training. The possibility of formation of model effects on the basis of joint use of multivariate dynamic databases and natural data simulator is shown. Dynamic databases store information that characterizes the typical representative situations of systems in the form of special functions - generating functions. Multiple variability of dynamic databases is determined by the type of the selected generating function, the methods of obtaining parameters (coefficients) of this function, as well as the selected accuracy of approximation. The situation models recovered by generating functions are used as basic components (trends) in the formation of the resulting full-scale - model implementations and are input into the natural data simulator. The data simulator allows for each variant of initial natural data to form an implementation of the perturbation signal with given statistical properties on a given simulation interval limited by the initial natural implementation. This is achieved with the help of a two-circuit structure, where the first circuit is responsible for evaluation and cor-rection of initial properties of the natural signal, and the second - for iterative correction of deviations of properties of the final implementation from the specified ones. The resulting realizations reflect the properties of their full-scale components, which are difficult to describe by analytical models, and are supplemented by model values, allowing in increments to correct the properties to the specified ones. The given approach allows to form set of variants of course of processes on the basis of one situation with different set degree of uncertainty and conditions of functioning.

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