Microlensing calculations with a hierarchical tree code: New results

2006 ◽  
pp. 186-191 ◽  
Author(s):  
Joachim Wambsganss
Keyword(s):  
Hierarchical Tree

scholarly journals BFIM: Performance Measurement of a Blockchain Based Hierarchical Tree Layered Fog-IoT Microservice Architecture

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Md Whaiduzzaman ◽  
Md. Julkar Nayeen Mahi ◽  
Alistair Barros ◽  
Md. Ibrahim Khalil ◽  
Colin Fidge ◽  
...  
Keyword(s):  
Performance Measurement ◽  
Hierarchical Tree ◽  
Microservice Architecture

scholarly journals Efficient alternatives to PSI-BLAST

2012 ◽  
Vol 60 (3) ◽  
pp. 495-505
Author(s):  
M. Startek ◽  
S. Lasota ◽  
M. Sykulski ◽  
A. Bułak ◽  
L. Noé ◽  
...  
Keyword(s):  
Amino Acid ◽  
Finite Automata ◽  
Protein Family ◽  
Homology Search ◽  
Amino Acid Residues ◽  
Protein Alignment ◽  
Substitution Model ◽  
Hierarchical Tree ◽  
Context Specific ◽  
Ncbi Blast

Abstract In this paper we present two algorithms that may serve as efficient alternatives to the well-known PSI BLAST tool: SeedBLAST and CTX-PSI Blast. Both may benefit from the knowledge about amino acid composition specific to a given protein family: SeedBLAST uses the advisedly designed seed, while CTX-PSI BLAST extends PSI BLAST with the context-specific substitution model. The seeding technique became central in the theory of sequence alignment. There are several efficient tools applying seeds to DNA homology search, but not to protein homology search. In this paper we fill this gap. We advocate the use of multiple subset seeds derived from a hierarchical tree of amino acid residues. Our method computes, by an evolutionary algorithm, seeds that are specifically designed for a given protein family. The seeds are represented by deterministic finite automata (DFAs) and built into the NCBI-BLAST software. This extended tool, named SeedBLAST, is compared to the original BLAST and PSI-BLAST on several protein families. Our results demonstrate a superiority of SeedBLAST in terms of efficiency, especially in the case of twilight zone hits. The contextual substitution model has been proven to increase sensitivity of protein alignment. In this paper we perform a next step in the contextual alignment program. We announce a contextual version of the PSI-BLAST algorithm, an iterative version of the NCBI-BLAST tool. The experimental evaluation has been performed demonstrating a significantly higher sensitivity compared to the ordinary PSI-BLAST algorithm.

Modeling and Designing of Urban Traffic Control Systems by Statecharts

2011 ◽  
Vol 308-310 ◽  
pp. 1582-1585
Author(s):  
Yi Sheng Huang ◽  
Tso Hsien Liao
Keyword(s):  
Boolean Function ◽  
Control Systems ◽  
Dynamic Model ◽  
Control Strategy ◽  
Traffic Control ◽  
Propositional Logic ◽  
Urban Traffic ◽  
Hierarchical Tree ◽  
Tree Diagram ◽  
Urban Traffic Control

Statechart has been utilized as a visual formalism for the modeling of complex systems. It illuminates the features on describing properties of causality, concurrency and synchronization. The reachability structure is used to represented dynamic model by a Boolean function. In this paper, we try to describe State invariant method and equation function for hierarchical tree diagram. Finally, we used them to analyze the urban traffic control systems which are modeled by using Statecharts. Their formalism provides a concept of propositional logic for presenting control strategy.

The role of constituent order and level of embedding in cross-linguistic structural priming

2016 ◽  
Vol 20 (2) ◽  
pp. 269-282 ◽  
Author(s):  
GUNNAR JACOB ◽  
KALLIOPI KATSIKA ◽  
NEILOUFAR FAMILY ◽  
SHANLEY E. M. ALLEN
Keyword(s):  
Priming Effect ◽  
Target Sentence ◽  
Structural Features ◽  
Structural Priming ◽  
Tree Representation ◽  
Priming Effects ◽  
Hierarchical Tree ◽  
Constituent Order

In two cross-linguistic priming experiments with native German speakers of L2 English, we investigated the role of constituent order and level of embedding in cross-linguistic structural priming. In both experiments, significant priming effects emerged only if prime and target were similar with regard to constituent order and also situated on the same level of embedding. We discuss our results on the basis of two current theoretical accounts of cross-linguistic priming, and conclude that neither an account based on combinatorial nodes nor an account assuming that constituent order is directly responsible for the priming effect can fully explain our data pattern. We suggest an account that explains cross-linguistic priming through a hierarchical tree representation. This representation is computed during processing of the prime, and can influence the formulation of a target sentence only when the structural features specified in it are grammatically correct in the target sentence.

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