Very Large Data Volumes Analysis of Collaborative Systems with Finite Number of States
Journal Title: Journal of Applied Quantitative Methods - Year 2010, Vol 5, Issue 1
Abstract
The collaborative system with finite number of states is defined. A very large database is structured. Operations on large databases are identified. Repetitive procedures for collaborative systems operations are derived. The efficiency of such procedures is analyzed.
Authors and Affiliations
Ion IVAN, Cristian CIUREA, Sorin PAVEL
Keywords
Related Articles
- EP ID EP150364
- DOI -
- Views 94
- Downloads 0
Halos and Horns in the Assessment of Undergraduate Medical Students: A Consistency-Based Approach
The authors introduce a consistency-based approach to detecting examiner bias. On comparing intra-class correlation coefficients on transformed data for supervisor continuous performance and report marks (ICC1*) with tho...
The International Conference “Innovation and Society 2011. Statistical Methods for the Evaluation of Services (IES 2011)”
During the last years, the attention of statisticians towards the instruments for the evaluation of services for the society has been increased. This phenomenon has been mostly due to the request of both the productive s...
Tendencies in the University System in Romania
Here is a short presentation of the main statistical indicators for higher education. The analysis was structured on the national and regional level and takes into account the differences between private and state univer...
Data Mining into the Websites of Management Institutes using Binary Representation
A similarity index is developed in this paper to measure the resemblance of information contained in the websites of several management institutes of India. The data matrix pertaining to information contents of the diffe...
A STEP-WISE METHOD FOR EVALUATION OF DIFFERENTIAL ITEM FUNCTIONING
Item bias or differential item functioning (DIF) has an important impact on the fairness of psychological and educational testing. In this paper, DIF is seen as a lack of fit to an item response (IRT) model. Inferences a...