Selection of Data Structures

1976 ◽  
pp. 45-50
Author(s):  
James Richard Low
Keyword(s):  
Data Structures ◽  
Selection Of

scholarly journals Compile- and run-time approaches for the selection of efficient data structures for dynamic graph analysis

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Benjamin Schiller ◽  
Clemens Deusser ◽  
Jeronimo Castrillon ◽  
Thorsten Strufe
Keyword(s):  
Data Structures ◽  
Graph Analysis ◽  
Dynamic Graph ◽  
Efficient Data ◽  
Run Time ◽  
Efficient Data Structures ◽  
Selection Of

scholarly journals Pengujian Black Box pada Aplikasi Sistem Penunjang Keputusan Seleksi Calon Pegawai Negeri Sipil Menggunakan Teknik Equivalence Partitions

2019 ◽  
Vol 4 (4) ◽  
pp. 131
Author(s):  
Misbah Syah Anwar Kesuma Jaya ◽  
Pandu Gumilang ◽  
Tresna Wati ◽  
Yohanes Philipus Andersen ◽  
Teti Desyani
Keyword(s):  
Software Testing ◽  
Data Structures ◽  
Support System ◽  
Black Box ◽  
Civil Servants ◽  
Error Models ◽  
Box Method ◽  
Selection Of

Support System for Decision on the Selection of Prospective Civil Servants is still an error when making changes to the data that has been entered, so that it can cause data can not be updated. So it needs to be tested to find problems with this software. Tests conducted on this software use the Black Box method based on Equivalence Partition as a whole with regard to the use, benefits, and results found from the use of the software. Equivalence Partition-based Black Box method tests the quality of the application that will be carried out by software testing documentation with the discovery of errors in each form that is divided into three error models, including errors in Functions, Data Structures and Interfaces. This test provides results where we will find out whether the software This has an error or not, and this test can guarantee the quality of this software.

scholarly journals The structure of Albanian personality descriptive trait-adjectives: A psycho-lexically based taxonomy

2020 ◽  
Vol 6 ◽  
pp. 1-11
Author(s):  
Rudina Ademi Shala ◽  
Boele De Raad ◽  
Aliriza Arënliu
Keyword(s):  
Data Structures ◽  
Big Five ◽  
Varimax Rotation ◽  
Full List ◽  
Negative Valence ◽  
Standard Procedures ◽  
Rating Process ◽  
Components Analysis ◽  
Positive Valence ◽  
Selection Of

In this study, we describe the taxonomy of personality descriptive trait terms in the Albanian language according to the psycho-lexical procedure, in two parts. In the first part the selection of trait terms from a standard Albanian dictionary took place, largely according to standard procedures. This resulted in a useful set of 607 personality relevant terms. In the second part this list of trait terms was administered to 497 participants to obtain self-ratings. During the rating process, participants could indicate their familiarity with the terms, leading to another reduction to a final set of 434 trait terms with self-ratings. Principal Components Analysis followed by Varimax rotation was applied both using raw data and using ipsatized data. Structures with one up to seven factors were discussed and represented in a hierarchy of factor solutions. As an aid to the interpretation of the factors, use was made of markers of the Big Five, selected from the full list of 434 terms. The most comprehensive and clearest structure was found with seven factors, which included the Big Five and both Negative Valence and Positive Valence.

Selection of representations for data structures

1977 ◽  
Vol 12 (8) ◽  
pp. 147-154 ◽  
Author(s):  
Stanley J. Rosenschein ◽  
Shmuel M. Katz
Keyword(s):  
Data Structures ◽  
Selection Of

Selection of representations for data structures

1977 ◽  
Author(s):  
Stanley J. Rosenschein ◽  
Shmuel M. Katz
Keyword(s):  
Data Structures ◽  
Selection Of

Selection of representations for data structures

1977 ◽  
pp. 147-154
Author(s):  
Stanley J. Rosenschein ◽  
Shmuel M. Katz
Keyword(s):  
Data Structures ◽  
Selection Of

scholarly journals Adaptive preconditioning for a stream of SLAEs

2021 ◽  
Vol 2099 (1) ◽  
pp. 012008
Author(s):  
A P Karpov ◽  
V A Erzunov ◽  
E B Shchanikova ◽  
Yu G Bartenev
Keyword(s):  
Iterative Methods ◽  
Data Structures ◽  
Nonlinear Problems ◽  
Newton Iteration ◽  
Time Dependent ◽  
Computation Step ◽  
The Given ◽  
Selection Of ◽  
The Way

Abstract The paper considers the way of reducing the time consumed to solve SLAEs with iterative methods by reusing the data structures obtained in the solution of a previous SLAE, or selecting a preconditioner from the available set of preconditioners to minimize the time of solving the next SLAEs. Such adaptive preconditioning is used to solve time-dependent nonlinear problems. SLAEs generated at the Newton iteration n-1 of every computation step are solved using the SLAE structure of the first Newton iteration and the selection of a preconditioner from the given set allows reducing the time of solving SLAEs of a varying complexity at different time steps. The adaptive preconditioning idea and its application are demonstrated for a stream of SLAEs in some RFNC-VNIIEF’s codes.

scholarly journals MONA Implementation Secrets

2000 ◽  
Vol 7 (40) ◽  
Author(s):  
Nils Klarlund ◽  
Anders Møller ◽  
Michael I. Schwartzbach
Keyword(s):  
Data Structures ◽  
Decision Procedures ◽  
Tree Automata ◽  
Worst Case ◽  
Case Complexity ◽  
Worst Case Complexity ◽  
Selection Of

The MONA tool provides an implementation of automaton-based decision procedures for the logics WS1S and WS2S. It has been used for numerous applications, and it is remarkably efficient in practice, even though it faces a theoretically non-elementary worst-case complexity. The implementation has matured over a period of six years. Compared to the<br />first naive version, the present tool is faster by several orders of magnitude. This speedup is obtained from many different contributions working on all levels of the compilation and execution of formulas. We present<br />an overview of MONA and a selection of implementation "secrets" that have been discovered and tested over the years, including formula reductions, DAGification, guided tree automata, three-valued logic, eager minimization, BDD-based automata representations, and cache-conscious data structures. We describe these techniques and quantify their respective effects by experimenting with separate versions of the MONA tool that in turn omit each of them.

The Impact of Using Incorrect Weights With the Multiple Membership Random Effects Model

Methodology ◽  
2014 ◽  
Vol 10 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Lindsey J. Wolff Smith ◽  
S. Natasha Beretvas
Keyword(s):  
Random Effects ◽  
Data Structures ◽  
Simulation Study ◽  
Future Research ◽  
Small Scale ◽  
Random Effects Model ◽  
Real Dataset ◽  
Multiple Membership ◽  
The Impact ◽  
Selection Of

The multiple membership random effects model (MMREM) is used to appropriately model multiple membership data structures. Use of the MMREM requires selection of weights reflecting the hypothesized contribution of each level two unit (e.g., school) and their descriptors to the level one outcome. This study assessed the impact on MMREM parameter and residual estimates of the choice of weight pattern used. Parameter and residual estimates resulting from use of different weight patterns were compared using a real dataset and a small-scale simulation study. Under the conditions examined here, results indicated that choice of weight pattern did not greatly impact relative parameter bias nor level two residuals’ ranks. Limitations and directions for future research are discussed.

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