An Efficient Implementation for MOLAP Basic Data Structure and Its Evaluation

2007 ◽  
pp. 288-299 ◽  
Author(s):  
K. M. Azharul Hasan ◽  
Tatsuo Tsuji ◽  
Ken Higuchi
Keyword(s):  
Data Structure ◽  
Efficient Implementation ◽  
Basic Data

scholarly journals Dynamic sampling from a discrete probability distribution with a known distribution of rates

2021 ◽  
Author(s):  
Federico D’Ambrosio ◽  
Hans L. Bodlaender ◽  
Gerard T. Barkema
Keyword(s):  
Data Structure ◽  
Probability Distribution ◽  
Data Structures ◽  
Basic Data ◽  
Constant Time ◽  
Discrete Probability ◽  
Minimum Rate ◽  
Discrete Probability Distribution ◽  
Expected Time ◽  
Rejection Method

AbstractIn this paper, we consider several efficient data structures for the problem of sampling from a dynamically changing discrete probability distribution, where some prior information is known on the distribution of the rates, in particular the maximum and minimum rate, and where the number of possible outcomes N is large. We consider three basic data structures, the Acceptance–Rejection method, the Complete Binary Tree and the Alias method. These can be used as building blocks in a multi-level data structure, where at each of the levels, one of the basic data structures can be used, with the top level selecting a group of events, and the bottom level selecting an element from a group. Depending on assumptions on the distribution of the rates of outcomes, different combinations of the basic structures can be used. We prove that for particular data structures the expected time of sampling and update is constant when the rate distribution follows certain conditions. We show that for any distribution, combining a tree structure with the Acceptance–Rejection method, we have an expected time of sampling and update of $$O\left( \log \log {r_{max}}/{r_{min}}\right) $$ O log log r max / r min is possible, where $$r_{max}$$ r max is the maximum rate and $$r_{min}$$ r min the minimum rate. We also discuss an implementation of a Two Levels Acceptance–Rejection data structure, that allows expected constant time for sampling, and amortized constant time for updates, assuming that $$r_{max}$$ r max and $$r_{min}$$ r min are known and the number of events is sufficiently large. We also present an experimental verification, highlighting the limits given by the constraints of a real-life setting.

Mix-Subdivision Dynamic Terrain Visualization Algorithm

2013 ◽  
Vol 756-759 ◽  
pp. 3372-3377 ◽  
Author(s):  
Xiao Hui Zhao ◽  
Bao Di Xie ◽  
De Peng Wan ◽  
Qing Yun Wang
Keyword(s):  
Data Structure ◽  
Real Time ◽  
Physical Model ◽  
Linear Interpolation ◽  
Basic Data ◽  
Visualization Method ◽  
The Real ◽  
Terrain Visualization ◽  
Simulation Systems ◽  
Dynamic Terrain

Dynamic Terrain is becoming more and more important in ground-based simulation systems. In military simulation systems, craters and ruts can improve the reality. In this paper, a dynamic terrain visualization method based on quadtree and multi-resolution voxel is presented in order to realize the real-time rendering for realistic craters in battlefield. Quadtree is selected as our basic data structure and mix-subdivided according to the size of the terrain. Scene tree is recursive subdivided according to both the distance between the node and camera and error criterion. Vertex is removed to solve the cracks and linear interpolation to solve popping in the algorithm. We also implement the visualization of craters through combining our algorithm with the physical model of craters based on multi-resolution voxel. The implementation results prove that the method are feasible and efficient.

scholarly journals Projektowanie metadanych w korpusie tekstów polskich do 1500 roku – wielopoziomowa struktura informacji

2020 ◽  
pp. 59-69
Author(s):  
Mariusz Leńczuk
Keyword(s):  
Data Structure ◽  
Text Classification ◽  
Basic Data ◽  
Factors Affecting ◽  
Polish Language ◽  
The Subject

The subject of research are selected metadata that should characterize the texts collected in the corpus of the oldest attestations of the Polish language. The author of the article compares and analyses the factors affecting the development of the basic data structure used in synchronic and diachronic corpora (author, title, date of the text, text channel, text classification, source of citation). Without those factors taken into account the disambiguation of the object in the database becomes impossible, and the use of grammatical information is unreliable and impractical. The result of the presented analysis is a proposal to extend the level of description for individual markers.

scholarly journals The Use of Python Tutor on Programming Laboratory Session: Student Perspectives

2017 ◽  
pp. 327-336 ◽  
Author(s):  
Oscar Karnalim ◽  
Mewati Ayub
Keyword(s):  
Data Structure ◽  
Student Perspectives ◽  
Basic Data ◽  
Educational Tools ◽  
Student Centered ◽  
Content Change ◽  
Variable Content ◽  
The Impact ◽  
Academic Year

Based on the fact that the impact of educational tools can only be accurately measured through student-centered evaluation, this paper proposes a long-term in-class evaluation for Python Tutor, a program visualization tool developed by Guo. The evaluation involves 53 students from 4 Basic Data Structure classes, which were held in the even semester of 2016/2017 academic year. It is conducted based on questionnaire survey asked to the students after they have used Python Tutor in their half of programming laboratory sessions. In general, there are three findings from this work. Firstly, Python Tutor helps students to complete programming laboratory tasks, specifically for Basic Data Structure material. Secondly, Python Tutor helps students to understand general programming aspects which are execution flow, variable content change, method invocation sequence, object reference, syntax error, and logic error. Finally, based on student perspectives, Python Tutor is a helpful tool positively affecting the students.

Lists: The Basic Data Structure

1998 ◽  
pp. 61-102
Author(s):  
Oliver Grillmeyer
Keyword(s):  
Data Structure ◽  
Basic Data

scholarly journals The Impact of Pair Programming on the Performance of Slow-Paced Students

2020 ◽  
Vol 44 (2) ◽  
pp. 211-229
Author(s):  
Mewati Ayub ◽  
Oscar Karnalim ◽  
Laurentius Risal ◽  
Maresha Caroline Wijanto
Keyword(s):  
Academic Performance ◽  
Data Structure ◽  
Undergraduate Students ◽  
Basic Data ◽  
Pair Programming ◽  
Theoretical Knowledge ◽  
Introductory Programming ◽  
The Impact

A study shows that pair programming can help slow-paced students in completing Introductory Programming assessment. This paper replicates the study on Data Structure course, in which the completion of the assessments does not only rely on logic but also theoretical knowledge. The aim is to check whether pair programming is still helpful on such new assessment characteristics. Three classes of Data Structure course with 14 teaching weeks and a total of 72 undergraduate students are considered in this study. Two of the classes are about Basic Data Structure while another one is the advanced one. Our evaluation shows that pair programming can help slow-paced students in both pair and individual academic performance. It also increases overall academic performance if the tasks are more logic oriented. Nevertheless, no benefits provided for fast-paced students paired to the slow-paced ones, even though all students appreciate the use of pair programming.

Sign in / Sign up

Export Citation Format

Share Document